{ "count" : 83701, "data" : [ { "id" : "6a2ca0a374d8ee00a09a2cd8", "title" : "Senior Quantitative Risk Strategist", "company" : "Binance. US", "industry" : "Product", "salary" : { "min" : 180000.0, "max" : 280000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Quantitative Risk Strategist in the US FinTech industry, adjusted for seniority and company size." }, "location" : "U.S. ", "locations" : [ "U.S. " ], "timestamp" : "2026-06-15T03:20:23.949", "fingerprint" : "dffe190734707ce386d9658fa79f71f6cb37aca2539a9b2a2158bfe26b2b2531", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/binance.us/2deb43d1-ea00-4cdc-910a-b100b604895f/application", "externalId" : "2deb43d1-ea00-4cdc-910a-b100b604895f", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, R, MATLAB, SQL, Machine learning", "professionalSkills" : [ "Risk analytics", "Fraud science", "Payments risk", "Risk modeling", "Data analysis", "Decision making" ], "hardSkillsList" : [ "Predictive modeling", "Quantitative analysis", "Statistical methods", "Anomaly detection", "Data analysis", "Risk assessment", "Model validation", "Model governance" ], "hardSkills" : [ { "name" : "Predictive modeling", "level" : "intermediate" }, { "name" : "Quantitative analysis", "level" : "intermediate" }, { "name" : "Statistical methods", "level" : "intermediate" }, { "name" : "Anomaly detection", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Risk assessment", "level" : "intermediate" }, { "name" : "Model validation", "level" : "intermediate" }, { "name" : "Model governance", "level" : "intermediate" } ], "majorSkills" : "Quantitative risk modeling, Payments risk strategy, Risk decisioning, Fraud prevention", "majorSkillsList" : [ "Quantitative risk modeling", "Payments risk strategy", "Risk decisioning", "Fraud prevention" ], "coreResponsibilities" : "Design predictive risk models, Develop predictive risk models, Deploy predictive risk models, Improve predictive risk models, Build customer-level models, Build transaction-level models, Build portfolio-level models, Develop risk segmentation frameworks, Apply statistical methods, Apply machine learning techniques, Apply anomaly detection, Apply large-scale data analysis, Quantify risk across payment rails, Monitor risk across payment rails, Develop forecasting methodologies, Establish key risk indicators, Establish operational thresholds, Establish portfolio health metrics, Establish executive reporting frameworks, Evaluate impact of new products, Evaluate impact of payment methods, Evaluate impact of customer segments, Evaluate impact of growth initiatives, Embed model-driven decisioning, Design risk rules, Test risk rules, Optimize risk rules, Design risk controls, Test risk controls, Optimize risk controls, Design decision engines, Test decision engines, Optimize decision engines, Design transaction monitoring systems, Test transaction monitoring systems, Optimize transaction monitoring systems, Lead champion/challenger testing, Lead experimentation frameworks, Measure effectiveness of risk controls, Drive continuous improvement, Quantify tradeoffs, Support data-driven decision making, Conduct deep-dive investigations, Identify root causes, Recommend corrective actions, Support model governance, Support model validation, Support model audit, Support regulatory review, Establish model performance monitoring, Establish model calibration, Establish backtesting processes, Serve as trusted advisor", "teamCollaboration" : "Partner with Product; Partner with Engineering; Partner with Risk; Partner with Compliance; Partner with Data; Partner with Operations", "domainKnowledge" : "Financial services; Fintech; Cryptocurrency; Payments risk; Fraud; ACH; Card payments; Transaction risk; Predictive modeling; Risk analytics; Financial crime risk", "domainList" : [ "financial-services", "fintech", "cryptocurrency", "payments-risk", "fraud", "ach", "card-payments", "transaction-risk", "predictive-modeling", "risk-analytics", "financial-crime-risk" ], "domainSpecificKnowledge" : [ "Financial services", "Fintech", "Cryptocurrency", "Payments risk", "Fraud", "ACH", "Card payments", "Transaction risk", "Predictive modeling", "Risk analytics", "Financial crime risk" ], "toolProficiency" : [ "Bloomberg Terminal", "Reuters Eikon", "FactSet" ], "documentationSkills" : "Comprehensive documentation", "problemSolvingSkills" : "Root cause analysis", "qualificationsBasic" : "8+ years quantitative risk analytics, 8+ years fraud science, 8+ years payments risk, 8+ years machine learning, 8+ years data science, 8+ years risk modeling", "qualificationsPreferred" : "Advanced degree in Statistics, Advanced degree in Mathematics, Advanced degree in Economics, Advanced degree in Finance, Advanced degree in Computer Science, Advanced degree in Physics, Advanced degree in Operations Research, Advanced degree in Data Science", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "About Binance.US: Binance.US is America’s home to buy, trade, and earn digital assets. As a licensed and regulated U.S. crypto platform, we provide secure, reliable access to more than 190 of the world’s most popular cryptocurrencies, all with some of the lowest fees in the industry. We’re a remote-first team of innovators building the bridge between traditional finance and Web3, helping bring financial freedom within reach for all. To learn more, visit www.binance.us http://www.binance.us. All roles supporting Binance.US http://Binance.US are employed via BAM Management US Holdings Inc. or BAM Management Canada Holdings Inc. About This Role: The Senior Quantitative Risk Strategist is part of the Product organization and serves as a senior individual contributor responsible for designing, developing, validating, and optimizing quantitative risk models and analytical frameworks that protect Binance.US http://Binance.US customers, payment systems, and operations from fraud, financial crimes, account compromise, and payment-related losses. This role will act as the quantitative lead for payments risk, partnering closely with Product, Risk, Compliance, Engineering, Data, and Operations teams to develop scalable, data-driven risk solutions across customer onboarding, account funding, trading, and withdrawal experiences. The ideal candidate combines deep expertise in predictive modeling and risk analytics with practical experience managing fraud, ACH, card, and transaction risk within highly regulated financial services, fintech, or cryptocurrency environments. Success in this role requires balancing customer growth, conversion, and user experience with loss prevention, regulatory obligations, and operational efficiency. Core Responsibilities: Quantitative Risk Modeling & Analytics - Design, develop, deploy, and continuously improve predictive risk models, scoring methodologies, and decision frameworks across ACH deposits, wire transfers, debit card funding, withdrawals, account security, fraud, and cryptocurrency-related risk domains. - Build customer-level, transaction-level, and portfolio-level models that predict fraud losses, payment returns, chargebacks, account compromise, and emerging risk events. - Develop risk segmentation frameworks that dynamically assess customer behavior throughout the customer lifecycle, including onboarding, funding, trading activity, and withdrawals. - Apply advanced statistical methods, machine learning techniques, anomaly detection, and large-scale data analysis to identify evolving fraud patterns, abuse vectors, and operational vulnerabilities. Payments Risk Strategy - Quantify and monitor risk across payment rails, including ACH, wire, card, and other funding methods. - Develop forecasting methodologies for payment losses, ACH return rates, chargebacks, fraud exposure, and emerging risk trends. - Establish key risk indicators (KRIs), operational thresholds, portfolio health metrics, and executive reporting frameworks. - Evaluate the impact of new products, payment methods, customer segments, and growth initiatives through rigorous quantitative risk assessment. Risk Decisioning & Optimization - Partner with Product and Engineering teams to embed model-driven decisioning throughout the customer journey. - Design, test, and optimize risk rules, controls, decision engines, and transaction monitoring systems to maximize fraud prevention while minimizing customer friction. - Lead champion/challenger testing and experimentation frameworks to measure the effectiveness of risk controls and drive continuous improvement. - Quantify tradeoffs between fraud loss, customer conversion, operational efficiency, and business growth to support data-driven decision making. Investigations & Risk Governance - Conduct deep-dive investigations into material fraud events, payment losses, suspicious activity, and operational incidents, identifying root causes and recommending corrective actions. - Support model governance, validation, audit, and regulatory review activities through comprehensive documentation, monitoring, and control frameworks. - Establish model performance monitoring, calibration, and backtesting processes to ensure ongoing effectiveness and compliance. - Serve as a trusted advisor to senior leadership on payments risk, fraud analytics, financial crime risk, and cryptocurrency-related risk trends. Preferred Skills/Experience: - 8+ years of experience in quantitative risk analytics, fraud science, payments risk, machine learning, data science, or risk modeling within fintech, financial services, payments, banking, or cryptocurrency organizations. - Advanced degree in Statistics, Mathematics, Economics, Finance, Computer Science, Physics, Operations Research, Data Science, or a related quantitative discipline. Equivalent industry experience building and deploying production risk models will be strongly considered. - Advanced proficiency in SQL and strong experience with Python, Spark, R, or comparable analytical and modeling technologies. - Demonstrated success designing, deploying, validating, and monitoring predictive risk models in production environments. - Deep understanding of ACH payments, return codes, chargebacks, account takeover risk, first-party fraud, synthetic identity fraud, mule activity, payment abuse, and transaction risk management. - Experience developing portfolio-level forecasting models for fraud losses, payment returns, chargebacks, or credit-related risk outcomes. - Strong knowledge of AML regulations, sanctions compliance, KYC/KYB requirements, and financial crime risk management. - Experience supporting model governance programs, audit reviews, regulatory examinations, and independent model validation activities. - Familiarity with blockchain analytics platforms, cryptocurrency transaction monitoring solutions, and digital asset risk indicators. - Strong communication skills with the ability to translate complex quantitative findings into actionable business recommendations for both technical and executive audiences. Our Mission: At Binance.US http://Binance.US, our mission is to create a more inclusive financial system through Web3 technologies. As a U.S. regulated crypto platform, we’re committed to earning trust through compliance and empowering people to do more with their money, bringing financial freedom within reach for all. Our Values: Our values shape how we work, make decisions, and support our users every day: - Act with Integrity: We do what’s right, even when no one is watching. - Be Collaborative: We work together with respect and transparency to achieve shared goals. - Customers First: We listen to, advocate for, and prioritize our users in every decision we make. - Do the Work: We take ownership, follow through, and deliver results that move the mission forward. - Embrace Change: We stay adaptable and curious, thriving in a fast moving industry. Our Benefits: We believe in supporting our people with flexibility, balance, and opportunities to grow. One of the ways we demonstrate this commitment is through our benefit offerings. - Time & Family: Unlimited PTO (for salaried FTE roles); 12 weeks fully paid Parental Bonding Leave. - Well-Being: Mental wellness benefits; free 1:1 virtual visits with a licensed mental wellness professional; comprehensive competitive health benefits. - Remote-First Culture: Fully remote, cameras-on culture with work-from-home equipment reimbursements available to new hires. - Professional & Financial Growth: Annual professional development budget; free 1:1 virtual visits with a career coach; 401k plan with employer match. BAM Management US Holdings Inc. and BAM Management Canada Holdings Inc. are Equal Opportunity Employers and comply with all applicable federal, state, and local fair employment practice laws. Our mission is to give our customers access to a broad array of digital assets, and we thrive because of the diverse and inclusive team that we are building. We do not discriminate against qualified employees, applicants, or any other covered persons because of race, color, religion, creed, gender identity, sex, sexual preference, sexual identity, pregnancy, national origin, ancestry, citizenship, age, veteran status, physical disability, mental disability, medical condition, military status, or any other applicable legally protected characteristic. Depending on your location, data privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available here https://www.binance.us/privacy-policy#employee-applicants-privacy-notice. By submitting your application, you are agreeing to our use and processing of your data as required. We comply with Federal Transparency in Coverage regulations by providing a link to machine readable files related to the health plans offered to our employees. The machine-readable files are formatted to allow researchers, regulators, and application developers to more easily access and analyze data including negotiated service rates, and out-of-network allowed amounts between health plans and healthcare providers.", "summaryDescription" : "Senior Quantitative Risk Strategist at Binance. US. Skills: Quantitative risk modeling, Payments risk strategy, Risk decisioning, Fraud prevention. Design predictive risk models. Develop predictive risk models", "createdAt" : "2026-06-13T21:29:56.504", "lastUpdated" : "2026-06-15T03:20:23.949", "ingestTimestamp" : "2026-06-13T21:29:56.504", "mongoId" : "6a2ca0a374d8ee00a09a2cd8", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 180000, "salaryAnnualMax" : 280000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Predictive modeling", "Quantitative analysis", "Statistical methods", "Anomaly detection", "Data analysis", "Risk assessment", "Model validation", "Model governance", "Quantitative risk modeling", "Payments risk strategy", "Risk decisioning", "Fraud prevention", "Risk analytics", "Fraud science", "Payments risk", "Risk modeling", "Decision making", "Financial services", "Fintech", "Cryptocurrency", "Fraud", "ACH", "Card payments", "Transaction risk", "Financial crime risk", "Bloomberg Terminal", "Reuters Eikon", "FactSet" ], "skillCount" : 28, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "_score" : 797.9109, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c5e3174d8ee00a08e2017", "title" : "Quantitative Analyst - Risk", "company" : "Graviton Research Capital LLP", "industry" : "Financial Services", "salary" : { "min" : 2500000.0, "max" : 4500000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market data for Quantitative Analyst roles in FinTech in Gurugram, India, adjusted for mid-seniority and company size." }, "location" : "Gurugram, Haryana, India", "locations" : [ "Gurugram", "Haryana", "India" ], "timestamp" : "2026-06-14T18:55:46.334", "fingerprint" : "abf4f86396a98064b906c019ed538c8f5e8883ade8d90334b45cd9569bb58736", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://boards.greenhouse.io/gravitonresearchcapital/jobs/8547628002?gh_jid=8547628002", "externalId" : "8547628002", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Gurugram", "state" : "Haryana", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "28.4646148,77.0299194" } ], "locationText" : "Gurugram, Haryana, India", "minimumEducation" : "Bachelor's", "experienceMinYears" : 3, "experienceMaxYears" : 5, "experienceLevel" : "Mid", "technicalSkills" : "Python, Shell scripting, C++, Linux", "professionalSkills" : [ "Risk attribution", "Performance break-ups", "Market data analysis" ], "hardSkillsList" : [ "Time series analysis", "Stochastic models", "Statistical inference", "Quantitative analysis" ], "softSkillsList" : [ "Mentoring" ], "hardSkills" : [ { "name" : "Time series analysis", "level" : "intermediate" }, { "name" : "Stochastic models", "level" : "intermediate" }, { "name" : "Statistical inference", "level" : "intermediate" }, { "name" : "Quantitative analysis", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Mentoring" } ], "majorSkills" : "Risk analysis, Trading strategies, Python scripting", "majorSkillsList" : [ "Risk analysis", "Trading strategies", "Python scripting" ], "coreResponsibilities" : "Operate automated trading strategies, Implement automated trading strategies, Improve automated trading strategies, Analyze production trades, Develop ideas to improve trading strategies, Implement monitoring tools, Highlight potential issues in production strategies, Write scalable scripts in C++, Write scalable scripts in Python, Analyze production strategies for risk attribution, Analyze production strategies for performance break-ups, Build scalable post-trade systems, Analyze statistics across production strategies, Implement tools for analyzing Market Data, Manage deployments, Manage release cycle", "teamCollaboration" : "Work with senior traders", "projectManagementSkills" : [ "Release cycle management" ], "domainKnowledge" : "Financial markets; Pricing anomalies; Asset classes", "domainList" : [ "financial-markets", "pricing-anomalies", "asset-classes" ], "domainSpecificKnowledge" : [ "Financial markets", "Pricing anomalies", "Asset classes" ], "toolProficiency" : [ "Linux command-line tools" ], "communicationSkills" : "Excellent communication", "documentationSkills" : "Comprehensive documentation", "problemSolvingSkills" : "Problem-solving skills", "qualificationsBasic" : "3+ years of experience in Python, 3+ years of experience in Shell scripting, Basic knowledge of Linux, Basic knowledge of shell command-line tools, Basic programming skills, Basic scripting skills, Analytical skills, Excellent communication skills, Have a work ethics, Mentorship experience", "qualificationsPreferred" : "Degree in Mathematics, Degree in Computer Science, Degree in Engineering", "workSiteFlexibility" : "Onsite", "rawDescription" : "Description: Graviton is a privately funded quantitative trading firm striving for excellence in financial markets' research. We are seeking a Quant Analyst - Risk for our team in Gurugram. Graviton trades across a multitude of asset classes and trading venues using a gamut of concepts and techniques ranging from time series analysis, filtering, classification, stochastic models, pattern recognition to statistical inference analysing terabytes of data to come up with ideas to identify pricing anomalies in financial markets. As a Quant Analyst - Risk you will be responsible Work as a team with senior traders to operate and implement/improve our automated trading strategies. Analysing production trades and developing ideas to improve our trading strategies. Implement monitoring tools which highlight potential issues in the production strategies. Write comprehensive and scalable scripts in both C++ and python analysing production strategies for risk attribution, performance break-ups along various buckets and so on. Build ‘cool’ scalable post-trade systems analysing multitude of statistics across all production strategies. Implementing tools for analysing Market Data centrally across various exchanges. Managing deployments and release cycle, with working along with a senior trader. Requirements : Possess a degree in a highly analytical field, such as Engineering, Mathematics, or Computer Science from top-ranked universities 3+ years of experience in Python, Shell/Bash scripting. Basic knowledge of Linux and shell command-line tools Basic programming and scripting (Python/Shell) skills Strong problem-solving, and analytical skills Excellent communication skills Have a strong work ethics Mentorship experience in guiding junior developers. Benefits: Our open and collaborative work culture gives you the freedom to innovate and experiment. Our cubicle free offices, non-hierarchical work culture and insistence to hire the very best creates a melting pot for great ideas and technological innovations. Everyone on the team is approachable, there is nothing better than working with friends! Our perks have you covered. Competitive compensation Annual international team outing Fully covered commuting expenses Best-in-class health insurance Delightful catered breakfasts and lunches A well-stocked kitchen 4 week annual leaves along with market holidays Gym and sports club memberships Regular social events and clubs After work parties", "summaryDescription" : "Quantitative Analyst - Risk at Graviton Research Capital LLP. Skills: Risk analysis, Trading strategies, Python scripting. Operate automated trading strategies. Implement automated trading strategies", "postedDate" : "2026-06-12T21:51:56.963", "createdAt" : "2026-06-12T21:51:56.963", "lastUpdated" : "2026-06-14T18:55:46.334", "ingestTimestamp" : "2026-06-12T21:51:56.963", "mongoId" : "6a2c5e3174d8ee00a08e2017", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Time series analysis", "Stochastic models", "Statistical inference", "Quantitative analysis", "Mentoring", "Risk analysis", "Trading strategies", "Python scripting", "Risk attribution", "Performance break-ups", "Market data analysis", "Release cycle management", "Financial markets", "Pricing anomalies", "Asset classes", "Linux command-line tools" ], "skillCount" : 16, "jobCategory" : "other", "jobSubcategory" : "quantitative-trading-", "dataQualityScore" : 0.8888889, "_score" : 774.33984, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Financial Services" }, { "id" : "6a2c7c2274d8ee00a094c659", "title" : "Product Analyst, Quantitative Equities", "company" : "Connor, Clark & Lunn Investment Management", "industry" : "FinTech", "salary" : { "min" : 125000.0, "max" : 200000.0, "currency" : "CAD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Vancouver, British Columbia, Canada", "locations" : [ "Vancouver", "British Columbia", "Canada" ], "certifications" : [ "CFA", "FRM" ], "timestamp" : "2026-06-16T04:05:21.995", "fingerprint" : "0a6e22741b0c6ac623428d3a10d3a5b720daf7eb93b00fbb01b97437031da4c5", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/cclim/jobs/4274259009", "externalId" : "4274259009", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Vancouver", "state" : "British Columbia", "country" : "Canada", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "49.2608724,-123.1139520" } ], "locationText" : "Vancouver, British Columbia, Canada", "employmentType" : "FULL_TIME", "experienceMinYears" : 2, "experienceMaxYears" : 5, "technicalSkills" : "Python, R, SQL", "professionalSkills" : [ "Quantitative analysis", "Financial modeling", "Data analysis" ], "hardSkillsList" : [ "Quantitative analysis", "Financial modeling", "Data analysis" ], "hardSkills" : [ { "name" : "Quantitative analysis", "level" : "intermediate" }, { "name" : "Financial modeling", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" } ], "majorSkills" : "Quantitative analysis, Financial modeling, Data analysis", "majorSkillsList" : [ "Quantitative analysis", "Financial modeling", "Data analysis" ], "coreResponsibilities" : "Develop and maintain quantitative models, Perform data analysis, Generate reports, Support trading strategies, Conduct market research, Collaborate with portfolio managers, Assist with risk management", "teamCollaboration" : "Portfolio managers; Traders; Risk management team", "domainKnowledge" : "Equities; Fixed income; Derivatives; Risk management; Quantitative finance", "domainList" : [ "equities", "fixed-income", "derivatives", "risk-management", "quantitative-finance" ], "domainSpecificKnowledge" : [ "Equities", "Fixed income", "Derivatives", "Risk management", "Quantitative finance" ], "toolProficiency" : [ "Bloomberg Terminal", "Reuters Eikon", "FactSet" ], "communicationSkills" : "Report generation; Presentation skills", "documentationSkills" : "Model documentation", "problemSolvingSkills" : "Quantitative analysis; Data analysis", "outcomesObjectives" : "Enhance investment strategies; Improve risk-adjusted returns; Provide timely market insights", "qualificationsBasic" : "2+ years experience, Bachelor's degree", "qualificationsPreferred" : "Master's degree preferred, CFA charterholder preferred, FRM certification preferred, Experience with Python preferred, Experience with R preferred, Experience with SQL preferred, Experience with Bloomberg Terminal preferred, Experience with Reuters Eikon preferred, Experience with FactSet preferred", "remoteFriendly" : false, "rawDescription" : "We are looking for a Product Analyst to support our globally recognized quantitative investment platform. We combine quantitative research with leading-edge technology to develop differentiated algorithmic investment strategies. A culture of innovation, growth and success through collaboration and mutual respect has enabled us to deliver top tier performance for over two decades. Today, our clients entrust us with over US$60 billion in assets under management across a range of investment mandates. The successful candidate will contribute directly to analysis and research that translate a quantitative investment process into clear, credible content for institutional investors. This is a high-impact role for someone who combines technical depth, sound judgment, and strong communication skills. What You Will Do Working closely with the Quantitative Equity, Client Solutions, and Institutional Sales teams, the Product Analyst will support a broad range of activities, including: Investment Content Development – Develop materials that resonate with internal/external stakeholders by clearly and succinctly relating a complex investment process to developments in markets and portfolios. Business Development – Support initiatives that contribute to the long-term growth and success of the Quantitative Equity platform. Cross-Team Engagement – Build strong relationships with internal stakeholders in order to improve systems, processes, and communications across teams. External Presence – Represent the Quantitative Equity team in meetings with institutional clients, prospects, and consultants. What You Bring Academic background in finance, economics, statistics, mathematics, engineering, data science or a related quantitative discipline. 2 – 5 years of work experience on a quantitative or systematic investment team. Working understanding of factor investing frameworks, portfolio construction and optimization principles, performance attribution and risk decomposition, and empirical research methods. Demonstrated ability to critically and creatively analyze large financial datasets, with a high level of attention to detail. Experience developing external-facing analysis or thought leadership, and ideally presenting this content to stakeholders. Exceptional written and verbal communication skills, with the ability to explain complex quantitative concepts clearly and concisely. A collaborative spirit that enables successful working relationships with a large number of internal and external stakeholders. CFA designation or progress toward completion is an asset. We welcome applications from candidates with different levels of experience. The base salary range is $125,000 – $200,000 annually plus a competitive performance bonus. Compensation will be determined based on experience and qualifications. To apply for this position, please submit your resume, cover letter and academic transcripts. We thank all applicants for their interest, however, only those selected for an interview will be contacted. No telephone calls or agencies will be accepted. Successful applicants must be eligible to work in Canada on their start date. CC&L Financial Group is committed to creating a diverse and inclusive environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to gender, ethnicity, religion, sexual orientation or expression, disability, or age.  Your application will be reviewed by a member of the hiring team - AI is not used in the screening, assessment or selection of applications at this time.", "summaryDescription" : "Product Analyst, Quantitative Equities at Connor, Clark & Lunn Investment Management. Skills: Quantitative analysis, Financial modeling, Data analysis. Develop and maintain quantitative models. Perform data analysis", "postedDate" : "2026-06-14T19:11:56.124", "createdAt" : "2026-06-14T19:11:56.124", "lastUpdated" : "2026-06-16T04:05:21.995", "ingestTimestamp" : "2026-06-14T19:11:56.124", "mongoId" : "6a2c7c2274d8ee00a094c659", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Quantitative analysis", "Financial modeling", "Data analysis", "Equities", "Fixed income", "Derivatives", "Risk management", "Quantitative finance", "CFA", "FRM", "Bloomberg Terminal", "Reuters Eikon", "FactSet" ], "skillCount" : 13, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Mid", "dataQualityScore" : 0.8888889, "_score" : 753.98615, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Financial Services", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6cd574d8ee00a091bab7", "title" : "Quantitative Product Development Engineer", "company" : "Metabit Technology LLC", "industry" : "FinTech", "salary" : { "min" : 480000.0, "max" : 720000.0, "currency" : "HKD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market data for a Junior Quantitative Product Development Engineer in FinTech in Hong Kong, adjusted for entry-level experience and company size." }, "location" : "Hong Kong", "locations" : [ "Hong Kong" ], "timestamp" : "2026-06-15T05:28:03.400", "fingerprint" : "73bbbe8cfdceac1356aa821169c29866ce189c7665fdbcb844c071fb9b9c4ec7", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/metabittechnologyllc/jobs/4265918009", "externalId" : "4265918009", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Hong Kong", "country" : "Hong Kong", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "22.2818333,114.1582831" } ], "locationText" : "Hong Kong, Hong Kong", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 2, "experienceMaxYears" : 2, "experienceLevel" : "Entry", "technicalSkills" : "C++, Python, Java, Go, Rust", "professionalSkills" : [ "System design", "Technical excellence" ], "hardSkillsList" : [ "Quantitative trading" ], "hardSkills" : [ { "name" : "Quantitative trading", "level" : "intermediate" } ], "majorSkills" : "Equity trading, Futures trading, Strategy deployment", "majorSkillsList" : [ "Equity trading", "Futures trading", "Strategy deployment" ], "coreResponsibilities" : "Develop trading products, Maintain trading products, Improve online service quality, Assume ownership of reliability, Collaborate with Quantitative Researchers, Facilitate deployment of strategies, Facilitate iteration of strategies, Ensure strategies execute efficiently, Generate substantial returns, Guarantee stable operation, Manage production incidents, Address critical emergency situations, Optimize system performance, Optimize computation performance, Optimize storage performance, Optimize networking performance, Optimize hardware resources performance", "teamCollaboration" : "Collaborate with Quantitative Researchers", "domainKnowledge" : "Equity trading; Futures trading; Financial trading systems; Post-trade workflow", "domainList" : [ "equity-trading", "futures-trading", "financial-trading-systems", "post-trade-workflow" ], "domainSpecificKnowledge" : [ "Equity trading", "Futures trading", "Financial trading systems", "Post-trade workflow" ], "toolProficiency" : [ "Git", "Code review", "CI/CD" ], "communicationSkills" : "Fluent in Chinese; Fluent in English", "outcomesObjectives" : "Generate substantial returns", "qualificationsBasic" : "Bachelor's degree or higher, Minimum of 2 years experience, Proficiency in Linux, Proficiency in C++, Proficiency in scripting language, Proficiency in Python 3, Proficiency in strongly typed language, Familiarity with production lifecycle, Familiarity with service reliability, Familiarity with Git, Familiarity with code review, Familiarity with CI/CD, Adept at building developer tools", "qualificationsPreferred" : "Award winners in ACM/ICPC, Award winners in NOI/NOIP, Experience maintaining mission-critical products, System design capabilities, Experience in financial trading systems, Experience in post-trade workflow development", "rawDescription" : "Responsibilities Deeply participate in the development and maintenance of equity and futures trading products. Continuously improve online service quality through technical engineering and assume ownership of the reliability of the live trading environment. Collaborate closely with Quantitative Researchers to facilitate the deployment and continuous iteration of diverse strategies at varying scales. Ensure these strategies execute efficiently in the production environment to generate substantial returns. Guarantee the stable operation of live trading systems. Manage production incidents during trading hours and maintain readiness to address critical emergency situations. Optimize the performance of trading and order execution systems across multiple dimensions, including computation, storage, networking, and hardware resources. Qualifications Bachelor’s degree or higher in Computer Science or a related field. Minimum of 2 years of relevant professional experience. Proficiency in the Linux operating system. Technical proficiency in at least one of the following): C++ and one scripting language. Python 3 and one strongly typed language (e.g., Java, Go, Rust). Familiarity with the full production lifecycle and iteration workflows of online services, with an understanding of technical methods to enhance service reliability. Familiarity with engineering best practices including Git, code review, and CI/CD. Adept at building developer tools with a pursuit of technical excellence. Strong interest in quantitative trading; fluent in both Chinese and English. Preferred Qualifications Award winners in ACM/ICPC, NOI/NOIP, or other major informatics competitions. Experience maintaining mission-critical products with high complexity and massive scale. Strong system design capabilities, with the ability to architect systems for performance, reliability, and availability. Experience in financial trading systems or post-trade workflow development.", "summaryDescription" : "Quantitative Product Development Engineer at Metabit Technology LLC. Skills: Equity trading, Futures trading, Strategy deployment. Develop trading products. Maintain trading products", "postedDate" : "2026-06-14T05:29:48.316", "createdAt" : "2026-06-14T05:29:48.316", "lastUpdated" : "2026-06-15T05:28:03.400", "ingestTimestamp" : "2026-06-14T05:29:48.316", "mongoId" : "6a2c6cd574d8ee00a091bab7", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Quantitative trading", "Equity trading", "Futures trading", "Strategy deployment", "System design", "Technical excellence", "Financial trading systems", "Post-trade workflow", "Git", "Code review", "CI/CD" ], "skillCount" : 11, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Junior", "dataQualityScore" : 1.0, "_score" : 735.6751, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c75ec74d8ee00a09388a3", "title" : "Quantitative Developer", "company" : "Poesis", "industry" : "Engineering", "salary" : { "min" : 180000.0, "max" : 280000.0, "currency" : "USD", "frequency" : "Yearly" }, "location" : "San Francisco", "locations" : [ "San Francisco" ], "timestamp" : "2026-06-16T02:57:35.521", "fingerprint" : "3b2dc2fae32d1b45fec189e17e460b6008dc79f71883911d9bec5cf31a69d6a2", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/poesis/95065a70-aa63-4469-b98c-087201a28d77/application", "externalId" : "95065a70-aa63-4469-b98c-087201a28d77", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Menlo Park", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "37.4519671,-122.1779920" } ], "locationText" : "Menlo Park, California, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "technicalSkills" : "Python, Pandas, Numpy, Scipy, Matplotlib, SQL, Claude Code, Codex", "professionalSkills" : [ "Feature generation", "Back-testing", "Model evaluation", "Data schemas", "APIs", "Reproducibility standards" ], "hardSkillsList" : [ "Statistics", "Regression", "Optimization", "ML fundamentals" ], "softSkillsList" : [ "Clear communicator" ], "hardSkills" : [ { "name" : "Statistics", "level" : "intermediate" }, { "name" : "Regression", "level" : "intermediate" }, { "name" : "Optimization", "level" : "intermediate" }, { "name" : "ML fundamentals", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Clear communicator" } ], "majorSkills" : "Quantitative research, Model implementation, Data pipelines", "majorSkillsList" : [ "Quantitative research", "Model implementation", "Data pipelines" ], "coreResponsibilities" : "Implement and iterate on research ideas, Implement model prototypes, Clean financial datasets, Process financial datasets, Join financial datasets, Build processes for feature generation, Build processes for back-testing, Build processes for model evaluation, Maintain processes for feature generation, Maintain processes for back-testing, Maintain processes for model evaluation, Run experiments, Summarize results, Report findings to leadership, Contribute to code quality, Support defining data schemas, Support defining APIs, Support defining reproducibility standards, Implement models, Test models, Refine models, Implement signals, Test signals, Refine signals, Implement analytical workflows, Test analytical workflows, Refine analytical workflows, Maintain consistent cadence of deliverables, Focus on iteration speed, Focus on reliability", "teamCollaboration" : "Engineering leadership; Chief Scientist; CEO", "domainKnowledge" : "Financial datasets; Portfolio optimization; Risk modeling; Financial time-series", "domainList" : [ "financial-datasets", "portfolio-optimization", "risk-modeling", "financial-time-series" ], "domainSpecificKnowledge" : [ "Financial datasets", "Portfolio optimization", "Risk modeling", "Financial time-series" ], "toolProficiency" : [ "Git", "Docker", "Prefect", "Airflow" ], "communicationSkills" : "Explain technical findings", "documentationSkills" : "Documentation", "innovationCreativity" : "Research ideas; Model prototypes", "problemSolvingSkills" : "Analytical workflows", "specialRequirements" : "Work visa sponsorship", "qualificationsBasic" : "Python skills, SQL comfort, Claude Code, Codex, or other coding agents skill, Real-world financial datasets proficiency, Reproducible analyses or pipelines building, Statistics understanding, Regression understanding, Optimization understanding, ML fundamentals understanding, Clear communicator, BS/MS/PhD in Computer Science, Mathematics, Statistics, Physics, Finance or related quantitative field", "qualificationsPreferred" : "Prior full-time experience in finance, data science, or ML engineering, Early-stage startup experience, Demonstrated builder mindset", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "ABOUT POESIS Whoever builds the leading intelligence for finance will create far more than returns. Poesis is the AI-native investment firm running autonomous agents that predict markets, construct portfolios, and manage risk. Our founders managed institutional capital at Capital Group ($3T AUM) and led enterprise ML at Goldman Sachs and Amazon. We're building a new type of firm, where live capital is the training ground for an intelligence that compounds with every signal. ABOUT THE ROLE We’re hiring a Quantitative Developer to help turn research ideas into production-grade code. You’ll help build data pipelines, implement models and ensure results are clean, reproducible and explainable. You’ll work alongside Poesis’ Chief Scientist, CEO and engineering leadership to turn large-scale data and quantitative research into models, signals and tools that drive investment decision-making. RESPONSIBILITIES - Rapidly implement and iterate on research ideas and model prototypes. - Clean, process, and join financial and fundamental datasets from professional and public sources. - Build and maintain processes for feature generation, back-testing, and model evaluation. - Run experiments, summarize results, and report findings to leadership. - Contribute to code quality: testing, documentation, and integration into shared systems. - Support the team in defining data schemas, APIs, and reproducibility standards. - Implement, test, and refine models, signals, and analytical workflows. - Maintain a consistent cadence of deliverables, focusing on iteration speed and reliability. REQUIRED COMPETENCIES - Strong Python skills (pandas, numpy, scipy, matplotlib); comfort with SQL. - Skill working with Claude Code, Codex, or other coding agents. - Proficiency working with real-world financial datasets and building reproducible analyses or pipelines. - Understanding of statistics, regression, optimization, and ML fundamentals. - Clear communicator who can explain technical findings to non-specialists. - BS/MS/PhD in Computer Science, Mathematics, Statistics, Physics, Finance or related quantitative field. PREFERRED COMPETENCIES - Prior full-time experience in finance, data science, or ML engineering. - Familiarity with APIs from Bloomberg, CapIQ, FactSet, or Refinitiv. - Exposure to portfolio optimization, risk modeling, or financial time-series. - Skill with git, Docker, and modern orchestration tools (Prefect, Airflow, etc.). - Early-stage startup experience or demonstrated builder mindset. LOCATION Hybrid: 3 days per week on-site at our office in Menlo Park, CA. Relocation allowance available. BENEFITS We offer excellent medical, dental, and vision coverage, alongside a strong benefits package that includes catered lunches in our Menlo Park office, commuter benefits, and more. Current legal authorization to work in the US required; continuing work visa sponsorship available for full-time employees. WORKING AT POESIS As an early team member, you’ll help shape not just the product, but how the company operates. Your decisions will have lasting impact across the business. You’ll build from first principles, with no legacy systems, or entrenched processes slowing you down. Our team is made up of people from elite companies and universities who are low ego, collaborative, and excited to build together.", "summaryDescription" : "Quantitative Developer at Poesis. Skills: Quantitative research, Model implementation, Data pipelines. Implement and iterate on research ideas. Implement model prototypes", "createdAt" : "2026-06-14T18:38:40.209", "lastUpdated" : "2026-06-16T02:57:35.521", "ingestTimestamp" : "2026-06-14T18:38:40.209", "mongoId" : "6a2c75ec74d8ee00a09388a3", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 180000, "salaryAnnualMax" : 280000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Statistics", "Regression", "Optimization", "ML fundamentals", "Clear communicator", "Quantitative research", "Model implementation", "Data pipelines", "Feature generation", "Back-testing", "Model evaluation", "Data schemas", "APIs", "Reproducibility standards", "Financial datasets", "Portfolio optimization", "Risk modeling", "Financial time-series", "Git", "Docker", "Prefect", "Airflow" ], "skillCount" : 22, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Mid", "dataQualityScore" : 0.7777778, "_score" : 720.58215, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c68ca74d8ee00a0904c50", "title" : "Quantitative Developer", "company" : "TradingHub", "industry" : "Analytics & Data", "salary" : { "min" : 95000.0, "max" : 135000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-level Quantitative Developer in London, UK, adjusted for the FinTech industry." }, "location" : "London", "locations" : [ "London" ], "timestamp" : "2026-06-16T03:36:13.356", "fingerprint" : "a5891dc60db14cae01d4de338056b5787054ced27c5889ecbb74887ecd41b7d6", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/tradinghub/10a15c19-9c9e-4dda-b95c-e2936d618dea/application", "externalId" : "10a15c19-9c9e-4dda-b95c-e2936d618dea", "industryFunction" : { }, "structuredLocations" : [ { "city" : "London", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "hybrid", "geo" : "51.5074456,-0.1277653" } ], "locationText" : "London, United Kingdom", "employmentType" : "FULL_TIME", "technicalSkills" : "C#, C++, Python", "professionalSkills" : [ "Financial modeling", "Risk algorithms" ], "hardSkillsList" : [ "Mathematical skills", "Analytical skills" ], "hardSkills" : [ { "name" : "Mathematical skills", "level" : "intermediate" }, { "name" : "Analytical skills", "level" : "intermediate" } ], "majorSkills" : "Quantitative development, Pricing models, Financial markets", "majorSkillsList" : [ "Quantitative development", "Pricing models", "Financial markets" ], "coreResponsibilities" : "Design pricing models, Build pricing models, Validate pricing models, Create financial pricing libraries, Create calculators, Create risk algorithms, Develop financial pricing libraries, Develop calculators, Develop risk algorithms, Use in-house big data language, Perform large-scale analysis, Productionize securities data, Research market dynamics, Develop market dynamics, Prototype proprietary models, Test proprietary models, Validate proprietary models", "teamCollaboration" : "Fast-paced environment", "domainKnowledge" : "Financial markets; Multiple asset classes; Risk sensitivities; Greeks; Delta; Gamma; DV01; Derivatives; Swaps; Options; Futures", "domainList" : [ "financial-markets", "multiple-asset-classes", "risk-sensitivities", "greeks", "delta", "gamma", "dv01", "derivatives", "swaps", "options", "futures" ], "domainSpecificKnowledge" : [ "Financial markets", "Multiple asset classes", "Risk sensitivities", "Greeks", "Delta", "Gamma", "DV01", "Derivatives", "Swaps", "Options", "Futures" ], "toolProficiency" : [ "Big data language" ], "continuousLearning" : "Study leave", "innovationCreativity" : "Experiment with new ideas", "problemSolvingSkills" : "Analytical skills", "qualificationsBasic" : "Proficiency with C#, C++ or Python, Exceptional mathematical and analytical skills, Initial industry experience as quant, Knowledge of risk sensitivities, Understanding of derivatives", "qualificationsPreferred" : "Capacity to put yourself in eyes of trader", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "Compensation: Competitive (Financial Services) About TradingHub Founded in 2010, TradingHub delivers uniquely intelligent trade surveillance software to world leading financial institutions. Developed by market professionals, our solutions use sophisticated modelling techniques to detect single and cross-product market manipulation. With a team of over 150 experts worldwide, TradingHub combines global reach with deep markets expertise to help our customers mitigate financial, regulatory, and reputational risk. The Role We are seeking a Quantitative Developer to contribute in designing, building and validating our pricing models. This includes creating financial pricing libraries for multiple asset classes, calculators and risk algorithms. The successful candidate will combine excellent mathematical skills with proven experience in financial markets and the ability to productionise high-quality software. The capacity to put yourself in the eyes of a trader will be very useful as we continue to ensure our product’s capabilities are ahead of competitors in the market. Responsibilities: - Development of financial pricing libraries, calculators as well as risk/pricing-related algorithms - Using our in-house big data language for the large-scale analysis and production of securities data - Research and development of market dynamics across multiple asset classes - Prototyping, testing, and validation of TradingHub’s proprietary models Requirements - Proficiency with C#, C++ or Python - Evidence of exceptional mathematical and analytical skills - Initial industry experience working as a quant within a financial services organisation - Some knowledge of risk sensitivities or \"Greeks\" such as Delta, Gamma, DV01 etc. - Understanding of derivatives (e.g. swaps, options, futures) - Confidence to experiment with new ideas and technologies - Keen to work in a fast-paced environment Benefits Life at TradingHub is a rewarding journey within a fast-growing company that thrives on innovation and collaboration. By combining the best of technology and global markets, we’re able to solve complex problems together and deliver meaningful results to our customers. Everybody has value to bring, and we welcome individuality as a key driving force behind our collective success. Rooted in everything that we do are our core values: Accountability, Ambition, Partnership and Trust. These values provide the foundation for a sustainable workplace culture that empowers you to grow, contribute, and become your best self. Employee Benefits: - Annual discretionary performance bonus (permanent employees only) - Hybrid working policy - Office lunches twice a week - Private medical insurance + dental cover - Extended parental leave (up to 6 months of fully paid maternity leave) - 25 days annual leave + bank holidays - Enhanced company pension plan - 5 days study leave towards professional qualifications - Salary sacrifice schemes - Death in service coverage Don’t tick every single requirement? Research shows that candidates from under-represented groups are less likely to apply unless they meet all the criteria. We are dedicated to building a diverse, equitable and inclusive workplace, so if this role excites you, please don't let our specification hold you back. Get in touch! TradingHub is an equal opportunities employer. We do not discriminate based on race, religion, ethnic or national origins, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, socio-economic background, responsibilities for dependants, physical or mental disability or other applicable legally protected characteristics. TradingHub selects candidates for interview based solely on their skills, experience and qualifications. We are committed to making our recruitment process accessible to all and we encourage candidates to inform us of any required adjustments. A full copy of our diversity, equity and inclusion policy will be made available to you upon request.", "summaryDescription" : "Quantitative Developer at TradingHub. Skills: Quantitative development, Pricing models, Financial markets. Design pricing models. Build pricing models", "createdAt" : "2026-06-14T19:20:30.123", "lastUpdated" : "2026-06-16T03:36:13.356", "ingestTimestamp" : "2026-06-14T19:20:30.123", "mongoId" : "6a2c68ca74d8ee00a0904c50", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "75k-100k", "hasSalary" : false, "allSkills" : [ "Mathematical skills", "Analytical skills", "Quantitative development", "Pricing models", "Financial markets", "Financial modeling", "Risk algorithms", "Multiple asset classes", "Risk sensitivities", "Greeks", "Delta", "Gamma", "DV01", "Derivatives", "Swaps", "Options", "Futures", "Big data language" ], "skillCount" : 18, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Mid", "dataQualityScore" : 0.7777778, "_score" : 718.7072, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6b5574d8ee00a09115d8", "title" : "Quantitative Trader", "company" : "Tower Research Capital", "industry" : "FinTech", "salary" : { "min" : 250000.0, "max" : 450000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Quantitative Trader in New York, adjusted for mid-seniority and FinTech industry." }, "location" : "New York, NY, United States", "locations" : [ "New York", "NY", "United States" ], "timestamp" : "2026-06-15T22:18:02.314", "fingerprint" : "07c3641e8501e6ed9094b06500d7942cae99bedbfbb61f0debdcaadebb167145", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://www.tower-research.com/open-positions/?gh_jid=8001169", "externalId" : "8001169", "industryFunction" : { }, "structuredLocations" : [ { "city" : "New York", "state" : "New York", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "40.7127281,-74.0060152" } ], "locationText" : "New York, New York, United States", "minimumEducation" : "Bachelor's", "remoteFriendly" : true, "rawDescription" : "Tower Research Capital is a leading quantitative trading firm founded in 1998. Tower has built its business on a high-performance platform and independent trading teams. We have a 25+ year track record of innovation and a reputation for discovering unique market opportunities. Tower is home to some of the world’s best systematic trading and engineering talent. We empower portfolio managers to build their teams and strategies independently while providing the economies of scale that come from a large, global organization. Engineers thrive at Tower while developing electronic trading infrastructure at a world class level. Our engineers solve challenging problems in the realms of low-latency programming, FPGA technology, hardware acceleration and machine learning. Our ongoing investment in top engineering talent and technology ensures our platform remains unmatched in terms of functionality, scalability and performance. At Tower, every employee plays a role in our success. Our Business Support teams are essential to building and maintaining the platform that powers everything we do — combining market access, data, compute, and research infrastructure with risk management, compliance, and a full suite of business services. Our Business Support teams enable our trading and engineering teams to perform at their best. At Tower, employees will find a stimulating, results-oriented environment where highly intelligent and motivated colleagues inspire each other to reach their greatest potential. Responsibilities Design, implement and deploy trading algorithms Support live trade strategies in production Research high to mid frequency alphas Explore trading ideas by analyzing market data, market microstructure and alternate data for patterns Present research results transparently and convincingly Create tools to analyze data for patterns and develop data platforms Contribute to libraries of analytical computations to support market data analysis and trading Develop, augment and calibrate exchange simulators Part-time work from home benefits Qualifications Bachelor’s degree or foreign equivalent in Mathematics, Statistics, Computer Science, or related STEM field Experience may be gained from coursework or internship. Must have experience with the following: Derivatives pricing and stochastic calculus Machine Learning including LLM Probability Theory Mathematics and statistics Back-testing, simulation, and statistical techniques, including auto-regression, auto-correlation and Principal Component Analysis Data mining and analysis skills, including experience dealing with a large amount of data Signal generation and statistical models Programming skills in Python or C++ Anticipated New York annual base salary range $125,000-$250,000, plus eligible for discretionary bonus. If interested, in addition to applying here you can email your resume indicating job # ID 00088964 to: Tower HR at us-ta@tower-research.com. Benefits Tower’s headquarters are in the historic Equitable Building, right in the heart of NYC’s Financial District and our impact is global, with over a dozen offices around the world. At Tower, we believe work should be both challenging and enjoyable. That is why we foster a culture where smart, driven people thrive – without the egos. Our open concept workplace, casual dress code, and well-stocked kitchens reflect the value we place on a friendly, collaborative environment where everyone is respected, and great ideas win. Our benefits include: Generous paid time off policies Savings plans and other financial wellness tools available in each region Hybrid working opportunities Free breakfast, lunch, and snacks daily In-office wellness experiences and reimbursement for select wellness expenses (e.g., gym, personal training and more) Company-sponsored sports teams and fitness events (JPM Corporate Challenge, Cycle for Survival, Wall Street Rides FAR and more) Volunteer opportunities and charitable giving Social events, happy hours, treats, and celebrations throughout the year Workshops and continuous learning opportunities At Tower, you’ll find a collaborative and welcoming culture, a diverse team and a workplace that values both performance and enjoyment. No unnecessary hierarchy. No ego. Just great people doing great work – together. Tower Research Capital is an equal opportunity employer. #LI-DNI", "summaryDescription" : "Quantitative Trader at Tower Research Capital", "postedDate" : "2026-06-14T18:00:11.985", "createdAt" : "2026-06-14T18:00:11.985", "lastUpdated" : "2026-06-15T22:18:02.314", "ingestTimestamp" : "2026-06-14T18:00:11.985", "mongoId" : "6a2c6b5574d8ee00a09115d8", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 250000, "salaryAnnualMax" : 450000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Mid", "dataQualityScore" : 0.6666667, "_score" : 700.4125, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c7c2b74d8ee00a094c82a", "title" : "Quantitative Researcher", "company" : "Man Group", "industry" : "FinTech", "salary" : { "min" : 220000.0, "max" : 350000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Quantitative Researcher in the United States, adjusted for Seniority, FinTech industry, and Massachusetts location." }, "location" : "Massachusetts", "locations" : [ "Massachusetts" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-15T05:05:00.246", "fingerprint" : "582ad6193055169e82de1f1852baa0dd22b6d1d356850c35985b0295491677d1", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/mangroup/jobs/4737145101", "externalId" : "4737145101", "industryFunction" : { }, "structuredLocations" : [ { "state" : "Massachusetts", "country" : "United States", "continent" : "na", "workMode" : "onsite" } ], "locationText" : "Massachusetts, United States", "minimumEducation" : "Master's", "technicalSkills" : "Python, R, SQL, Spark, Snowflake, BigQuery, Redshift, Databricks, Dbt, Fivetran, Airflow, Delta Lake, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, GCP, Azure", "professionalSkills" : [ "Alpha research", "Monetization algos", "Execution algos", "Market impact modelling", "Quantitative analysis", "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills" ], "hardSkillsList" : [ "Statistics", "Machine learning", "Programming", "Data handling", "Tick data analysis", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference" ], "softSkillsList" : [ "Intellectual integrity", "Interpersonal adaptability" ], "hardSkills" : [ { "name" : "Statistics", "level" : "intermediate" }, { "name" : "Machine learning", "level" : "intermediate" }, { "name" : "Programming", "level" : "intermediate" }, { "name" : "Data handling", "level" : "intermediate" }, { "name" : "Tick data analysis", "level" : "intermediate" }, { "name" : "Regression", "level" : "intermediate" }, { "name" : "Classification", "level" : "intermediate" }, { "name" : "Clustering", "level" : "intermediate" }, { "name" : "Time-series analysis", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Intellectual integrity" }, { "name" : "Interpersonal adaptability" } ], "majorSkills" : "Quantitative research, Machine learning, Data science, Algorithmic trading", "majorSkillsList" : [ "Quantitative research", "Machine learning", "Data science", "Algorithmic trading" ], "coreResponsibilities" : "Conduct alpha research, Design monetization algos, Design execution algos, Model market impact, Apply statistics to problems, Apply ML to problems, Handle large data sets, Handle tick data", "teamCollaboration" : "Close collaboration; Quantitative researchers; Technologists; Traders; Business people", "projectManagementSkills" : [ "Time management" ], "domainKnowledge" : "Alternative investment; Systematic strategies; Market structure; Trading venues; Asset classes; Cash Equities; Futures; FX; Options; High-frequency trading; Microstructure", "domainList" : [ "alternative-investment", "systematic-strategies", "market-structure", "trading-venues", "asset-classes", "cash-equities", "futures", "fx", "options", "high-frequency-trading", "microstructure" ], "domainSpecificKnowledge" : [ "Alternative investment", "Systematic strategies", "Market structure", "Trading venues", "Asset classes", "Cash Equities", "Futures", "FX", "Options", "High-frequency trading", "Microstructure" ], "toolProficiency" : [ "Python", "R", "Tableau", "Power BI", "Looker", "Snowflake", "BigQuery", "Redshift", "Databricks", "Dbt", "Fivetran", "Airflow", "MLflow", "SageMaker", "Vertex AI", "ML Studio" ], "communicationSkills" : "Argue a point; Deal with views", "continuousLearning" : "Professional development", "problemSolvingSkills" : "Analytic approach; Problem solving", "outcomesObjectives" : "Maximise realized P", "qualificationsBasic" : "Master's qualification, Quantitative subject, Analytic approach, Programming language, Python/R, Handling large data, Tick data", "qualificationsPreferred" : "PhD qualification, Knowledge of market structure, Knowledge of trading venues, Knowledge of microstructure, Experience in intraday alpha research, Experience in building ML models, GCP Professional Data Engineer, AWS Data Analytics, Databricks Certified, Dbt Certified", "workSiteFlexibility" : "Flexible", "rawDescription" : "About Man Group Man Group is a global alternative investment management firm focused on pursuing outperformance for sophisticated clients via our Systematic, Discretionary and Solutions offerings. Powered by talent and advanced technology, our single and multi-manager investment strategies are underpinned by deep research and span public and private markets, across all major asset classes, with a significant focus on alternatives. Man Group takes a partnership approach to working with clients, establishing deep connections and creating tailored solutions to meet their investment goals and those of the millions of retirees and savers they represent. Headquartered in London, we manage $227.6 billion* and operate across multiple offices globally. Man Group plc is listed on the London Stock Exchange under the ticker EMG.LN and is a constituent of the FTSE 250 Index. Further information can be found at www.man.com * As at 31 December 2025 Algo Research Team Algo Research team is responsible for alpha research across a wide range of time-scales (from high-frequency up to ~48 hours), design of monetization/execution algos and market impact modelling across all major asset classes (including Cash Equities, Futures, FX, Options). We work in close collaboration with various systematic research teams across Man Group to maximise realized P recognised by peers as an expert in one’s domain Deep understanding of statistics/ML and an ability to apply it to real world problems Expertise in a high-level programming language such as Python/ R Advantageous Knowledge of market structure, participants, trading venues and microstructure of at least one of the major asset classes Experience in intraday alpha research Experience in building ML models Experience with handling large data sets and tick data Personal Attributes PhD or exceptional Masters / Bachelor’s qualification in a quantitative subject Intellectual integrity with a keenly analytic approach to problem solving Ability to deliver projects with high commercial value Hands-on attitude; willing to get involved with technology and projects across the firm Self-organised with the ability to effectively manage time across multiple projects and with competing business demands and priorities Strong interpersonal skills; adaptability and ability to establish and maintain a close working relationship with quantitative researchers, technologists, traders and senior business people alike Confident communicator, able to argue a point concisely and deal positively with conflicting views The anticipated based salary range for this position is listed below. Compensation packages would also include benefits and a discretionary bonus. This is the base salary range that the Company believes it will pay for this position at the time of this posting based on the location and requirements of the position as well as the skills, qualifications, and experience of the applicant. The Firm reserves the right to modify this pay range at any time. US Pay Range $120,000—$140,000 USD Inclusion, Work-Life Balance and Benefits at Man Group You'll thrive in our working environment that champions equality of opportunity. Your unique perspective will contribute to our success, joining a workplace where inclusion is fundamental and deeply embedded in our culture and values. Through our external and internal initiatives, partnerships and programmes, you'll find opportunities to grow, develop your talents, and help foster an inclusive environment for all across our firm and industry. Learn more at www.man.com/diversity. You'll have opportunities to make a difference through our charitable and global initiatives, while advancing your career through professional development, and with flexible working arrangements available too. Like all our people, you'll receive two annual 'Mankind' days of paid leave for community volunteering. Our comprehensive benefits package includes competitive holiday entitlements, pension/401k, life and long-term disability coverage, group sick pay, enhanced parental leave and long-service leave. Depending on your location, you may also enjoy additional benefits such as private medical coverage, discounted gym membership options and pet insurance. Equal Employment Opportunity Policy Man Group provides equal employment opportunities to all applicants and all employees without regard to race, color, creed, national origin, ancestry, religion, disability, sex, gender identity and expression, marital status, sexual orientation, military or veteran status, age or any other legally protected category or status in accordance with applicable federal, state and local laws. Man Group is a Disability Confident Committed employer; if you require help or information on reasonable adjustments as you apply for roles with us, please contact TalentAcquisition@man.com.", "summaryDescription" : "Quantitative Researcher at Man Group. Skills: Quantitative research, Machine learning, Data science, Algorithmic trading. Conduct alpha research. Design monetization algos", "postedDate" : "2026-06-14T08:18:55.572", "createdAt" : "2026-06-14T08:18:55.572", "lastUpdated" : "2026-06-15T05:05:00.246", "ingestTimestamp" : "2026-06-14T08:18:55.572", "mongoId" : "6a2c7c2b74d8ee00a094c82a", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 220000, "salaryAnnualMax" : 350000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Statistics", "Machine learning", "Programming", "Data handling", "Tick data analysis", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference", "Intellectual integrity", "Interpersonal adaptability", "Quantitative research", "Data science", "Algorithmic trading", "Alpha research", "Monetization algos", "Execution algos", "Market impact modelling", "Quantitative analysis", "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills", "Time management", "Alternative investment", "Systematic strategies", "Market structure", "Trading venues", "Asset classes", "Cash Equities", "Futures", "FX", "Options", "High-frequency trading", "Microstructure", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "Python", "R", "Tableau", "Power BI", "Looker", "Snowflake", "BigQuery", "Redshift", "Databricks", "Dbt", "Fivetran", "Airflow", "MLflow", "SageMaker", "Vertex AI", "ML Studio" ], "skillCount" : 58, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Senior", "dataQualityScore" : 0.7777778, "_score" : 688.5597, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.98 }, { "id" : "69fc49a74c40e2acd1a83413", "title" : "Sr. Quantitative Modeler", "company" : "Hyundai Capital America", "industry" : "FinTech", "salary" : { "min" : 155000.0, "max" : 215000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market data for a Senior Quantitative Modeler in Irvine, United States, adjusted for industry and company size." }, "location" : "United States-California-Irvine", "locations" : [ "United States-California-Irvine", "
Headquarters 1 (HCA_HQ1)
3161 Michelson Dr. Ste 1900
Irvine, 92612

" ], "timestamp" : "2026-06-15T08:02:58.393", "fingerprint" : "21242e381c0de76f297b61be4db279eb8c3438c6272bff61c4cd73830f01790d", "source" : "taleo", "language" : "en", "applyUrl" : "https://hyundaicapital.taleo.net/careersection/ex/jobdetail.ftl?job=113547", "externalId" : "113547", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Irvine", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "33.6856969,-117.8259810" } ], "locationText" : "Irvine, California, United States", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "SAS, Python, R, Machine Learning, Artificial Intelligence", "professionalSkills" : [ "Model development", "Model implementation", "Model monitoring", "Data quality validation" ], "hardSkillsList" : [ "Predictive modeling", "Statistical analysis", "Generalized regression", "Survival analysis", "Sampling design", "Hypothesis testing", "Stochastic processes" ], "hardSkills" : [ { "name" : "Predictive modeling", "level" : "intermediate" }, { "name" : "Statistical analysis", "level" : "intermediate" }, { "name" : "Generalized regression", "level" : "intermediate" }, { "name" : "Survival analysis", "level" : "intermediate" }, { "name" : "Sampling design", "level" : "intermediate" }, { "name" : "Hypothesis testing", "level" : "intermediate" }, { "name" : "Stochastic processes", "level" : "intermediate" } ], "majorSkills" : "Quantitative modeling, Credit risk, Machine Learning", "majorSkillsList" : [ "Quantitative modeling", "Credit risk", "Machine Learning" ], "coreResponsibilities" : "Lead design and development of predictive models, Provide analytic solutions, Support business functions, Implement models, Monitor models, Maintain model production processes, Perform additional analysis, Support business functions, Partner with auditors, Partner with model validation, Partner with legal, Partner with compliance, Partner with accounting, Ensure regulatory compliance, Adhere to internal policies, Partner with IT, Partner with data engineering, Partner with EDW teams, Validate data quality, Improve data quality", "teamCollaboration" : "Partner with internal stakeholders; Partner with external stakeholders; Partner with IT teams; Partner with data engineering; Partner with EDW teams", "domainKnowledge" : "Credit risk; Credit bureau data; Regulatory requirements; Market trends; Financial industry; Auto industry", "domainList" : [ "credit-risk", "credit-bureau-data", "regulatory-requirements", "market-trends", "financial-industry", "auto-industry" ], "domainSpecificKnowledge" : [ "Credit risk", "Credit bureau data", "Regulatory requirements", "Market trends", "Financial industry", "Auto industry" ], "communicationSkills" : "Translate concepts to insights", "problemSolvingSkills" : "Analytical methods; Analytic techniques", "qualificationsBasic" : "8 years predictive modeling experience, 5 years financial auto industry experience, Master's degree in quantitative fields, Proficiency in statistical programming, Proficiency in Machine Learning algorithms", "qualificationsPreferred" : "Ph. D. preferred, GCP Professional Data Engineer, AWS Data Analytics, Databricks Certified, Dbt Certified", "remoteFriendly" : false, "workSiteFlexibility" : "Flexible", "rawDescription" : "Who We Are Through our service brands Hyundai Motor Finance, Genesis Finance, and Kia Finance, Hyundai Capital America offers a wide range of financial products tailored to meet the needs of Hyundai, Genesis, and Kia customers and dealerships. We provide vehicle financing, leasing, subscription, and insurance solutions to over 3 million consumers and businesses. Embodying our commitment to grow, innovate, and diversify, we strive to reimagine the customer and dealer experience and launch innovative new products that broaden our market reach. We believe that success comes from within and are proud to support our team members through skill development and career advancement. Hyundai Capital America is an Equal Opportunity Employer committed to creating a diverse and inclusive culture for our workforce. We are a values-driven company dedicated to supporting both internal and external communities through volunteering, philanthropy, and the empowerment of our Employee Resource Groups. Together, we strive to be the leader in financing freedom of movement. We Take Care of Our People Along with competitive pay, as an employee of HCA, you are eligible for: · Medical, dental, and vision plans with no-cost and low-cost options · Annual employer HSA contribution · 401(k) matching and immediate vesting · Vehicle purchase and lease discounts, plus monthly vehicle allowances by job level: o Associate / Sr. Associate: $350 o Manager / Sr. Manager: $600 o Director: $800 o Executive Director: $900 o VP or Above: $1,000 · 100% employer-paid life and disability insurance · No-cost health and wellbeing programs, including a gym benefit · Six weeks of paid parental leave · Paid Volunteer Time Off, plus a company donation to a charity of your choice What to Expect The Sr. Quantitative Modeler will act as a lead modeler in the research and development of predictive quantitative models and delivering model-related analytic support. This position provides technical and methodological leadership and expertise for the application of advanced analytic methods and techniques in the business environment. What You Will Do · Lead the design and development of predictive models and provide analytic solutions to support business functions including model implementation and monitoring. · Maintain model production processes and perform additional analysis as needed to support business functions across HCA. · Partner with internal and external auditors, model validation, legal and compliance, accounting, and other stakeholders to ensure regulatory compliance and adherence to internal policies. · Partner with IT, data engineering and EDW teams to validate and improve data quality. What You Will Bring · Minimum 8 years predictive modeling experience with focus on credit risk, credit bureau data, regulatory requirements, market trends including 5 years within the financial and auto industry. · Master’s degree in quantitative fields such as Statistics, Data Science, Economics, Econometrics, Mathematics. · Ph.D. preferred. · Deep understanding of statistical and data science, theoretical foundations and techniques, such as generalized regression, survival analysis, sampling design, hypothesis testing, stochastic processes etc. · Proficiency in Machine Learning algorithms and models, and familiarity with Artificial Intelligence approaches and platforms. · Financial and auto industry knowledge, including credit risk, credit bureau data, regulatory requirements, market trends. · Ability to translate abstract statistical concepts and analytic results into actionable business insights. · Proficiency in statistical programming utilizing SAS, Python, R or other related software and platforms. · Strong communication and collaboration skills. · Attention to detail and timelines. Work Environment Employees in this class are subject to extended periods of sitting, standing, and walking, vision to monitor and moderate noise levels. Work is performed in an at home and office environment. The posted salary range for this job takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; geographic location, and other business and organizational needs. Successful candidates may be hired anywhere in the salary range based on these factors. It is uncommon to hire candidates at or near the top of the range. California Privacy Notice This notice only applies to our applicants who reside in the State of California. The latest version of our Privacy Policy can be found here . This Privacy Policy provides you with notice, at or before the point of collection, about the categories of personal information to be collected from you, the purposes for which your personal information is collected or used, and whether that information is sold or shared, so that you can exercise meaningful control over our use of your personal information. We are providing this notice to comply with the California Consumer Privacy Act of 2018, as amended as amended by the California Privacy Rights Act of 2020 (“CCPA”). If you have any questions about CCPA regarding California residents or HCA team members, please contact the Privacy Team at Privacy2@hcs.com . United States-California-Irvine", "summaryDescription" : "Sr. Quantitative Modeler at Hyundai Capital America. Skills: Quantitative modeling, Credit risk, Machine Learning. Lead design and development of predictive models. Provide analytic solutions", "createdAt" : "2026-06-14T00:47:29.049", "lastUpdated" : "2026-06-15T08:02:58.393", "ingestTimestamp" : "2026-06-14T00:47:29.049", "mongoId" : "69fc49a74c40e2acd1a83413", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 155000, "salaryAnnualMax" : 215000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Predictive modeling", "Statistical analysis", "Generalized regression", "Survival analysis", "Sampling design", "Hypothesis testing", "Stochastic processes", "Quantitative modeling", "Credit risk", "Machine Learning", "Model development", "Model implementation", "Model monitoring", "Data quality validation", "Credit bureau data", "Regulatory requirements", "Market trends", "Financial industry", "Auto industry" ], "skillCount" : 19, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Senior", "dataQualityScore" : 0.7777778, "_score" : 671.3246, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c7fe674d8ee00a0956d12", "title" : "Associate/AVP, Quantitative Strategies Group", "company" : "Cross River", "industry" : "Banking", "salary" : { "min" : 150000.0, "max" : 190000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Fort Lee, New Jersey, United States", "locations" : [ "Fort Lee", "New Jersey", "United States" ], "timestamp" : "2026-06-16T03:27:15.846", "fingerprint" : "4f97d293c1f8b38069b3ea3bc93c6b9f40783a060390e5524c40c2a045012cdc", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://www.crossriver.com/greenhouse?gh_jid=7770430003", "externalId" : "7770430003", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Fort Lee", "state" : "New Jersey", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.8509333,-73.9701382" } ], "locationText" : "Fort Lee, New Jersey, United States", "employmentType" : "FULL_TIME", "rawDescription" : "Who We Are Cross River builds the infrastructure behind the world’s most innovative financial products. Our technology and capital solutions power payments, cards, lending, and digital asset capabilities that move money safely, instantly, and inclusively — trusted by leading fintechs, enterprises, and disruptors across the globe. Our mission is simple: to build the financial infrastructure that expands access and opportunity for all. Guided by a culture of collaboration, curiosity, and purpose, Cross River has been named one of American Banker’s Best Places to Work in Fintech year after year. Whether you’re designing code, solving regulatory puzzles, or developing strategy, you’ll join a team where innovation and integrity drive everything we do — and where your work helps shape the future of finance. What We're Looking For The Quantitative Strategies Group (QSG) at Cross River is seeking an Associate/AVP, Quant Strategist to join its growing team. The team sits within the Capital Solutions Group (CSG) and serves as a centralized function for investment intelligence and quantitative decision making across investment, structuring, and portfolio management initiatives. The role sits at the intersection of structured finance, investment strategy, and advanced analytics - bridging the gap between raw data and capital decisions. The role will work closely with the Structured Products Group (SPG) and Principal Finance Group (PFG) to support investment underwriting, new deal origination, term ABS issuance/advisory, and active portfolio management. The ideal candidate will combine strong analytical and technical skills with commercial judgement - someone who can analyze collateral performance, understand relevant risk factors, form a view on underlying assets, build scalable analytical tools, and translate complex quantitative outputs into clear investment recommendations. This is a high-impact role for someone who wants exposure to live transactions, structured credit markets, and data-driven decision-making. Responsibilities: Work closely with SPG and PFG to provide quantitative and analytical insights across investment opportunities, ABS securitizations, and structured credit transactions - from deal inception through execution Support capital commitment objectives through systematic underwriting of investment opportunities. Deliver refined and polished views on analytics, base/stress assumptions, and cashflow models that accurately capture the risk/reward dynamics of potential trades Support investment advisory mandates by producing market-ready analytics, comparative deal analyses, and performance benchmarks that help articulate differentiated value proposition to clients and counterparties Develop and maintain analytical frameworks to evaluate collateral pools, form views on key pricing assumptions (e.g., prepayment speeds, default/loss curves), and deliver actionable insights that inform deal economics and structuring decisions Translate quantitative outputs into clear/concise narratives and presentation materials that support pitch efforts, client discussions, and internal committees Partner with the team to identify, prioritize, and integrate high-impact AI use cases across workflows. Explore and implement AI-driven approaches to collateral analysis using LLMs and Python based tools Partner with other functions within CSG and across the bank to ensure consistency in assumptions, methodologies, and market intelligence used across the group Qualifications: Master’s degree in financial engineering, math, statistics, computer science, or any another quantitative/analytical field required 3+ years of experience in Structured Finance, Securitization, or broader Fixed Income markets is required. Direct exposure to ABS products is strongly preferred Strong understanding of cashflow modeling and securitization mechanics - deal waterfalls, tranche structures, collateral performance analysis is preferred Proficiency in advanced excel & programming is required for this role. Hands-on experience in Python & SQL is critical for success Excellent communication and presentation skills - ability to distill complex analytics into clear, persuasive narratives for both internal stakeholders and external counterparties Builder's mentality - someone who doesn't just use existing tools but actively seeks to improve how the team works by introducing new technologies, frameworks, and AI-driven efficiencies Ability to thrive in a fast-paced, deal-driven environment with competing priorities and tight turnaround times Detail-oriented with strong organizational skills and a proactive, ownership-driven mindset #LI-JJ1 #LI-Hybrid #LI-Onsite Salary Range: $150,000.00 - $190,000.00 Cross River is an Equal Opportunity Employer. Cross River does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need. By submitting your application, you give Cross River permission to email, call, or text you using the contact details provided. We will only contact you with job related information.", "summaryDescription" : "Associate/AVP, Quantitative Strategies Group at Cross River", "postedDate" : "2026-06-14T21:31:33.591", "createdAt" : "2026-06-14T21:31:33.591", "lastUpdated" : "2026-06-16T03:27:15.846", "ingestTimestamp" : "2026-06-14T21:31:33.591", "mongoId" : "6a2c7fe674d8ee00a0956d12", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 150000, "salaryAnnualMax" : 190000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Mid", "dataQualityScore" : 0.7777778, "_score" : 671.16516, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.97 }, { "id" : "6a2c96fa74d8ee00a09910b7", "title" : "Graduate Quantitative Researcher", "company" : "IMC", "industry" : "FinTech", "salary" : { "min" : 105000.0, "max" : 135000.0, "currency" : "CHF", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for entry-level Quantitative Researchers in Zug, Switzerland, adjusted for the FinTech industry and company size." }, "location" : "Zug, Switzerland", "locations" : [ "Zug", "Switzerland" ], "timestamp" : "2026-06-16T02:14:32.543", "fingerprint" : "d0dbd340ee76e4df11ba4008a8228eefb70ea2846950eb08bf306a98b9f7b594", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/imc/jobs/4892687101", "externalId" : "4892687101", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Zug", "country" : "Switzerland", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "47.1486137,8.5539378" } ], "locationText" : "Zug, Switzerland", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 0, "experienceMaxYears" : 2, "experienceLevel" : "Entry", "technicalSkills" : "Python, C++", "professionalSkills" : [ "Quantitative analysis", "Data analysis" ], "hardSkillsList" : [ "Quantitative methods" ], "hardSkills" : [ { "name" : "Quantitative methods", "level" : "intermediate" } ], "majorSkills" : "Quantitative research, Data analysis, Model development", "majorSkillsList" : [ "Quantitative research", "Data analysis", "Model development" ], "coreResponsibilities" : "Research trading ideas, Test trading ideas, Analyse datasets, Build models, Test models, Improve models, Build signals, Test signals, Improve signals, Build algorithms, Test algorithms, Improve algorithms, Work with data infrastructure, Work with software infrastructure, Work with HPC infrastructure, Collaborate with researchers, Collaborate with developers, Collaborate with engineers, Turn research into strategies, Evaluate trading opportunities", "teamCollaboration" : "Collaborate with researchers; Collaborate with developers; Collaborate with engineers", "domainKnowledge" : "Financial markets; Trading; Cryptocurrency; DeFi; Quantitative trading", "domainList" : [ "financial-markets", "trading", "cryptocurrency", "defi", "quantitative-trading" ], "domainSpecificKnowledge" : [ "Financial markets", "Trading", "Cryptocurrency", "DeFi", "Quantitative trading" ], "problemSolvingSkills" : "Problem-solving skills", "qualificationsBasic" : "Final-year student or recent graduate, Mathematics, Statistics, Physics, Computer Science, Engineering or related quantitative field, Analytical and problem-solving skills, Programming experience, Quantitative methods to real-world problems", "qualificationsPreferred" : "Python programming experience, C++ familiarity, Prior experience in trading, crypto, or financial markets", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "As a Graduate Quantitative Researcher, you will work with experienced researchers and developers in a fast-paced, data-driven environment. You will learn how trading ideas are researched, tested, and deployed, while contributing to live strategy development from early in your career. Your Core Responsibilities: Research and test data-driven trading ideas Analyse large and complex datasets from cryptocurrency exchanges, DeFi protocols, and financial markets Build, test, and improve models, signals, and algorithms that support trading strategies Work with IMC’s cutting-edge data, software, and high-performance computing infrastructure Collaborate closely with researchers, developers, and engineers to turn research into production-ready strategies Learn how to evaluate trading opportunities with a focus on performance, scalability, robustness, and risk Your Skills and Experience: Final-year student or recent graduate in Mathematics, Statistics, Physics, Computer Science, Engineering or a related quantitative field Strong analytical and problem-solving skills, with the ability to learn quickly Programming experience, ideally in Python. Familiarity with C++ is a plus A genuine interest in financial markets, trading, crypto, or DeFi Comfortable working with data and applying quantitative methods to real-world problems Curious, collaborative, and eager to take ownership in a fast-moving environment Prior experience in trading, crypto, or financial markets is helpful but not required. This is an on-site role based in Zug, Switzerland, with very limited flexibility for working from home. About Us IMC is a global trading firm powered by a cutting-edge research environment and a world-class technology backbone. Since 1989, we’ve been a stabilizing force in financial markets, providing essential liquidity upon which market participants depend. Across our offices in the US, Europe, Asia Pacific, and India, our talented quant researchers, engineers, traders, and business operations professionals are united by our uniquely collaborative, high-performance culture, and our commitment to giving back. From entering dynamic new markets to embracing disruptive technologies, and from developing an innovative research environment to diversifying our trading strategies, we dare to continuously innovate and collaborate to succeed.", "summaryDescription" : "Graduate Quantitative Researcher at IMC. Skills: Quantitative research, Data analysis, Model development. Research trading ideas. Test trading ideas", "postedDate" : "2026-06-14T20:07:21.715", "createdAt" : "2026-06-14T20:07:21.715", "lastUpdated" : "2026-06-16T02:14:32.543", "ingestTimestamp" : "2026-06-14T20:07:21.715", "mongoId" : "6a2c96fa74d8ee00a09910b7", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Quantitative methods", "Quantitative research", "Data analysis", "Model development", "Quantitative analysis", "Financial markets", "Trading", "Cryptocurrency", "DeFi", "Quantitative trading" ], "skillCount" : 10, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 1.0, "_score" : 668.35864, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a307f7bf292fd229c059dce", "title" : "Senior Product Quantitative Researcher, Cloud Security", "industry" : "Cybersecurity", "salary" : { "min" : 175000.0, "max" : 250000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Product Quantitative Researcher in Seattle, adjusted for the technology industry and senior experience level." }, "location" : "[Seattle, WA, USA, [Seattle, WA, USA], Seattle, null, WA, US]", "locations" : [ "[Seattle, WA, USA, [Seattle, WA, USA], Seattle, null, WA, US]", "[Sunnyvale, CA, USA, [Sunnyvale, CA, USA], Sunnyvale, null, CA, US]" ], "timestamp" : "2026-06-16T12:01:16.494", "fingerprint" : "0940d5d15d8053e7be136776c68e5de4d622fbba139a2457d359d3090e86ac22", "source" : "google", "language" : "en", "externalId" : "95723233260511942", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Seattle", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6038321,-122.3300620" } ], "locationText" : "Seattle, Washington, United States", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "summaryDescription" : "Senior Product Quantitative Researcher, Cloud Security", "postedDate" : "2026-06-16T01:52:16.510", "createdAt" : "2026-06-16T01:52:16.510", "lastUpdated" : "2026-06-16T12:01:16.494", "ingestTimestamp" : "2026-06-16T01:52:16.510", "mongoId" : "6a307f7bf292fd229c059dce", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 175000, "salaryAnnualMax" : 250000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "product", "jobSubcategory" : "product_management", "seniorityLevel" : "Senior", "dataQualityScore" : 0.5555556, "_score" : 655.34625, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c7c2b74d8ee00a094c82c", "title" : "Quantitative Research Intern", "company" : "Man Group", "industry" : "FinTech", "salary" : { "min" : 100000.0, "max" : 150000.0, "currency" : "HKD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market data for entry-level quantitative research internships in Hong Kong, adjusted for the FinTech industry and a large global company like Man Group." }, "location" : "Hong Kong", "locations" : [ "Hong Kong" ], "timestamp" : "2026-06-16T03:10:51.149", "fingerprint" : "38b47e2d37b5d92275bf11ea9647c03a066bb9fd5d5b5207ebf97a49ff2fe9d4", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/mangroup/jobs/4847714101", "externalId" : "4847714101", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Hong Kong", "country" : "Hong Kong", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "22.2818333,114.1582831" } ], "locationText" : "Hong Kong, Hong Kong", "employmentType" : "INTERNSHIP", "minimumEducation" : "Bachelor's", "technicalSkills" : "Python, Pandas, Numpy, Time-series methods, Statistical techniques, Machine learning models", "professionalSkills" : [ "Quantitative research", "Systematic equity research", "Alpha signal development", "Medium-frequency trading", "Statistical arbitrage" ], "hardSkillsList" : [ "Data analysis", "Signal construction", "Backtesting", "Overfitting diagnosis" ], "softSkillsList" : [ "Critical thinking", "Mentorship" ], "hardSkills" : [ { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Signal construction", "level" : "intermediate" }, { "name" : "Backtesting", "level" : "intermediate" }, { "name" : "Overfitting diagnosis", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Critical thinking" }, { "name" : "Mentorship" } ], "majorSkills" : "Quantitative research, Machine learning, Statistical analysis", "majorSkillsList" : [ "Quantitative research", "Machine learning", "Statistical analysis" ], "coreResponsibilities" : "Research time-series methods, Research advanced statistical techniques, Research machine learning models, Extract predictive value from datasets, Analyze noisy datasets, Identify systematic trading opportunities, Develop statistical tools, Develop ML-based tools, Solve data-related problems, Prototype signal variants, Document work cleanly", "teamCollaboration" : "Day-to-day mentorship; Core supervision; High-level exposure; Discuss research results; Present research results; Incorporate feedback", "projectManagementSkills" : [ "End-to-end research project ownership" ], "domainKnowledge" : "Systematic equity; Alpha signals; Medium-frequency; Statistical arbitrage; Predictive value; Systematic trading; Complex datasets; Real-world data", "domainList" : [ "systematic-equity", "alpha-signals", "medium-frequency", "statistical-arbitrage", "predictive-value", "systematic-trading", "complex-datasets", "real-world-data" ], "domainSpecificKnowledge" : [ "Systematic equity", "Alpha signals", "Medium-frequency", "Statistical arbitrage", "Predictive value", "Systematic trading", "Complex datasets", "Real-world data" ], "communicationSkills" : "Communicate complex results; Present research results", "documentationSkills" : "Document work cleanly", "continuousLearning" : "Mentorship", "problemSolvingSkills" : "Rigorous backtesting; Diagnosing overfitting; Questioning assumptions", "outcomesObjectives" : "Iterate towards deployable outcomes", "qualificationsBasic" : "Bachelor's in computer science, Bachelor's in statistics, Bachelor's in machine learning, Bachelor's in signal processing, Bachelor's in optimization, Bachelor's in mathematics, Bachelor's in physics, Master's in computer science, Master's in statistics, Master's in machine learning, Master's in signal processing, Master's in optimization, Master's in mathematics, Master's in physics, PhD in computer science, PhD in statistics, PhD in machine learning, PhD in signal processing, PhD in optimization, PhD in mathematics, PhD in physics, Proficiency in Python, Solid understanding of data structures, Solid understanding of algorithmic complexity, Solid understanding of numerical libraries, Demonstrated ability to conduct research, Ability to communicate complex results", "qualificationsPreferred" : "PhD preferred, Specific ML framework experience, Cloud platform certs", "workSiteFlexibility" : "Flexible", "rawDescription" : "About Man Group Man Group is a global alternative investment management firm focused on pursuing outperformance for sophisticated clients via our Systematic, Discretionary and Solutions offerings. Powered by talent and advanced technology, our single and multi-manager investment strategies are underpinned by deep research and span public and private markets, across all major asset classes, with a significant focus on alternatives. Man Group takes a partnership approach to working with clients, establishing deep connections and creating tailored solutions to meet their investment goals and those of the millions of retirees and savers they represent. Headquartered in London, we manage $227.6 billion* and operate across multiple offices globally. Man Group plc is listed on the London Stock Exchange under the ticker EMG.LN and is a constituent of the FTSE 250 Index. Further information can be found at www.man.com * As at 31 December 2025 Location: Hong Kong SAR Duration: 3–4 months, starting 2026 Eligibility: Final year students (Bachelor's, Master's, or PhD) The Team Join the Specialist Equities team, a small and collaborative systematic equity research group focused on developing medium-frequency statistical arbitrage alpha signals. You will receive day-to-day mentorship from a quantitative researcher in Hong Kong, with core supervision and high-level exposure to portfolio managers and senior management in London. Position Overview You will own a research project end-to-end, taking a disciplined scientific approach to form hypotheses, construct signals, and iterate towards deployable outcomes. The project scope is defined on our side and will be closely tailored to your specific background and strengths once we've met you. During the internship, you will: Research time-series methods, advanced statistical techniques, and machine learning models to extract predictive value from complex datasets. Analyze large, noisy, real-world data sets to identify systematic trading opportunities. Help develop statistical and ML-based tools and techniques to solve complex data-related problems throughout the research process. Typical Day Your primary focus throughout the day will be on researching new statistical techniques, exploring datasets, and prototyping signal variants. Apply critical thinking at every step—rigorously backtesting ideas, diagnosing overfitting, and questioning your own assumptions. Discuss and present research results with your immediate team, portfolio managers, and senior management, actively incorporating their feedback. Document your work cleanly and clearly so colleagues can easily build upon your findings. Required Qualifications Quantitative Background: Pursuing a Bachelor's, Master's, or PhD in computer science, statistics, machine learning, signal processing, optimization, mathematics, physics, or a related STEM subject. Research Excellence: Demonstrated ability to conduct high-quality, in-depth, and rigorous research on real-world data, along with the ability to communicate complex results clearly to both technical peers and senior stakeholders. Programming Proficiency: Strong proficiency in Python, with a solid understanding of data structures, algorithmic complexity, and numerical libraries (e.g., pandas, numpy). Statistical if you require help or information on reasonable adjustments as you apply for roles with us, please contact TalentAcquisition@man.com.", "summaryDescription" : "Quantitative Research Intern at Man Group. Skills: Quantitative research, Machine learning, Statistical analysis. Research time-series methods. Research advanced statistical techniques", "postedDate" : "2026-06-14T19:12:32.693", "createdAt" : "2026-06-14T19:12:32.693", "lastUpdated" : "2026-06-16T03:10:51.149", "ingestTimestamp" : "2026-06-14T19:12:32.693", "mongoId" : "6a2c7c2b74d8ee00a094c82c", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Data analysis", "Signal construction", "Backtesting", "Overfitting diagnosis", "Critical thinking", "Mentorship", "Quantitative research", "Machine learning", "Statistical analysis", "Systematic equity research", "Alpha signal development", "Medium-frequency trading", "Statistical arbitrage", "End-to-end research project ownership", "Systematic equity", "Alpha signals", "Medium-frequency", "Predictive value", "Systematic trading", "Complex datasets", "Real-world data" ], "skillCount" : 21, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 654.8711, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2cdb6a74d8ee00a0a504d7", "title" : "Associate Risk Engineer (Underwriter), Executive Risks", "company" : "Coalition, Inc.", "industry" : "Insurance", "salary" : { "min" : 60000.0, "max" : 80000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "United States - Remote", "locations" : [ "United States - Remote" ], "certifications" : [ "CFA", "FRM" ], "timestamp" : "2026-06-15T09:23:46.912", "fingerprint" : "228ebadf7e56e4e6f3eef4fcd29eee015874510fc76c12069e930aa5b8b44f13", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://www.coalitioninc.com/job-posting?gh_jid=4705637005", "externalId" : "4705637005", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "FULL_TIME", "technicalSkills" : "Python, R, SQL, Bloomberg Terminal, Reuters Eikon, FactSet", "professionalSkills" : [ "Risk assessment", "Underwriting", "Financial analysis" ], "hardSkillsList" : [ "Quantitative analysis", "Financial modeling" ], "hardSkills" : [ { "name" : "Quantitative analysis", "level" : "intermediate" }, { "name" : "Financial modeling", "level" : "intermediate" } ], "majorSkills" : "Executive Risks, Underwriting, Risk management", "majorSkillsList" : [ "Executive Risks", "Underwriting", "Risk management" ], "coreResponsibilities" : "Support renewal goals, Support new business goals, Manage tight time frames, Manage high volumes of work, Manage direct agency relationships", "teamCollaboration" : "Direct agency relationships", "domainKnowledge" : "Executive Risks; Financial lines products; Digital risk; Cybersecurity", "domainList" : [ "executive-risks", "financial-lines-products", "digital-risk", "cybersecurity" ], "domainSpecificKnowledge" : [ "Executive Risks", "Financial lines products", "Digital risk", "Cybersecurity" ], "toolProficiency" : [ "Bloomberg Terminal", "Reuters Eikon", "FactSet" ], "qualificationsBasic" : "5+ years experience", "qualificationsPreferred" : "CFA charterholder preferred, FRM charterholder preferred", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "About us Coalition is the world's first Active Insurance provider designed to help prevent digital risk before it strikes. Founded in 2017, Coalition combines comprehensive insurance coverage and innovative cybersecurity tools to help businesses manage and mitigate potential cyberattacks. Opportunities to make an impact with bold thinking are real—and happening daily at Coalition. About the role We are looking for an Underwriter to join our Executive Risks underwriting team to support the achievement of established renewal and new business goals for financial lines products, including D must be able to demonstrate success with managing tight time frames, high volumes of work, direct agency relationships Compensation Our compensation reflects the cost of labor across several US geographic markets. The US base salary for this position ranges from $60,000/year in our lowest geographic market up to $80,000/year in our highest geographic market. Consistent with applicable laws, an employee's pay within this range is based on a number of factors, which include but are not limited to relevant education, skills, job-related knowledge, qualifications, work experience, credentials, and/or geographic location. Your recruiter can share more on target salary for your location during the interview process. Coalition, Inc. reserves the right to modify this range as needed. Perks 100% medical, dental and vision coverage Flexible PTO policy Annual home office stipend and WeWork access Mental & physical health wellness programs (One Medical, Headspace, Wellhub, and more)! Competitive compensation and opportunity for advancement Why Coalition? Work at Coalition is centered on the joint mission to Protect the Unprotected. We have built a remote-first, highly inclusive culture that welcomes people from diverse backgrounds. We trust each other to take responsibility, share ownership of outcomes, and put in the work together to protect businesses from digital risk. Coalition’s exceptional growth stems from its ability to address real-world problems for organizations of all sizes while remaining true to our founding values of character, humility, responsibility, purpose, authenticity, and inclusion. We’re always looking for collaborative, inquisitive individuals to join #OurCoalition. Visit our Newsroom > Privacy Notice Coalition is committed to protecting your privacy and handling your personal information responsibly. We collect, use, and store personal information as necessary for the recruitment process and in compliance with applicable privacy laws and regulations in all regions where we operate. We want you to understand what personal information we collect, how we use it, and your rights regarding access, correction, and deletion of your data where applicable. Information submitted, collected, and processed as part of your application is subject to Coalition's Privacy Policy. For further details, please review our full Privacy Policy or contact us with any questions regarding how your information is handled. Our Privacy Policy > Safe Hiring Notice All legitimate communication from Coalition comes from @coalitioninc.com emails, and open roles are listed only on our Careers page. We never ask for payment, banking details, or personal identification before an offer is accepted through our secure systems. If you believe you’ve been a victim of fraudulent recruiting, follow guidance from the Federal Trade Commission (FTC). Anti-Discrimination Notice Coalition is proud to be an Equal Opportunity employer. Our policy is to provide equal employment opportunities to all individuals, without discrimination or harassment on the basis of any characteristic protected by applicable laws in each country where we operate. This commitment includes, but is not limited to, ensuring equal treatment in recruitment, selection, training, promotion, transfer, compensation, and all other aspects of employment. Coalition does not tolerate discrimination or harassment of any kind, and we are dedicated to fostering an inclusive and supportive workplace. Accommodations Coalition is committed to providing reasonable accommodations to qualified individuals with disabilities, including applicants and employees, in accordance with applicable laws and regulations in each country where we operate. Our policy is to support equal opportunity in the hiring process by considering qualified applicants regardless of disability or other protected characteristics, unless providing accommodation would impose an undue hardship or disproportionate burden. If you require accommodation to complete an application, interview, pre-employment testing, or participate in the selection process, please contact us at candidateaccommodations@coalitioninc.com. We also consider all qualified applicants, including those with criminal histories, in line with applicable laws and regulations in each jurisdiction. To all recruitment agencies: Coalition does not accept unsolicited agency resumes. Do not forward resumes to our email alias, employees, or other physical or virtual organization locations. Coalition is not responsible for any fees related to unsolicited resumes.", "summaryDescription" : "Associate Risk Engineer (Underwriter), Executive Risks at Coalition, Inc.. Skills: Executive Risks, Underwriting, Risk management. Support renewal goals. Support new business goals", "postedDate" : "2026-06-14T04:09:36.436", "createdAt" : "2026-06-14T04:09:36.436", "lastUpdated" : "2026-06-15T09:23:46.912", "ingestTimestamp" : "2026-06-14T04:09:36.436", "mongoId" : "6a2cdb6a74d8ee00a0a504d7", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 60000, "salaryAnnualMax" : 80000, "salaryBand" : "50k-75k", "hasSalary" : true, "allSkills" : [ "Quantitative analysis", "Financial modeling", "Executive Risks", "Underwriting", "Risk management", "Risk assessment", "Financial analysis", "Financial lines products", "Digital risk", "Cybersecurity", "CFA", "FRM", "Bloomberg Terminal", "Reuters Eikon", "FactSet" ], "skillCount" : 15, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Junior", "dataQualityScore" : 0.8888889, "_score" : 654.4418, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Insurance", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c7c2274d8ee00a094c65d", "title" : "Quantitative Equity Analyst", "company" : "Connor, Clark & Lunn Investment Management", "industry" : "FinTech", "salary" : { "min" : 125000.0, "max" : 200000.0, "currency" : "CAD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Vancouver, British Columbia, Canada", "locations" : [ "Vancouver", "British Columbia", "Canada" ], "certifications" : [ "CFA" ], "timestamp" : "2026-06-15T07:14:36.772", "fingerprint" : "23f99dcaeae28cdf3eadb256f67fc80e83c18ce04f3c1a1bcf06a56004856462", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/cclim/jobs/4223780009", "externalId" : "4223780009", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Vancouver", "state" : "British Columbia", "country" : "Canada", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "49.2608724,-123.1139520" } ], "locationText" : "Vancouver, British Columbia, Canada", "employmentType" : "FULL_TIME", "technicalSkills" : "Python, R, Scala, Spark, SQL, Dbt, Tableau, Power BI, Looker, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Delta Lake, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, GCP, Azure", "professionalSkills" : [ "Process engineering", "Data analysis", "Data expertise", "Data quality assessment", "Data scrubbing", "Data integration", "Financial theory", "Economic models", "Corporate financial statements" ], "hardSkillsList" : [ "Quantitative analysis", "Statistical validation", "Process management systems", "Algorithmic construction", "Data validation", "Data analysis", "Time series analysis", "Regression", "Classification", "Clustering", "A/B testing", "Causal inference" ], "softSkillsList" : [ "Analytical Mindset", "Collaborative Approach", "Time Management" ], "hardSkills" : [ { "name" : "Quantitative analysis", "level" : "intermediate" }, { "name" : "Statistical validation", "level" : "intermediate" }, { "name" : "Process management systems", "level" : "intermediate" }, { "name" : "Algorithmic construction", "level" : "intermediate" }, { "name" : "Data validation", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Time series analysis", "level" : "intermediate" }, { "name" : "Regression", "level" : "intermediate" }, { "name" : "Classification", "level" : "intermediate" }, { "name" : "Clustering", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Analytical Mindset" }, { "name" : "Collaborative Approach" }, { "name" : "Time Management" } ], "majorSkills" : "Quantitative finance, Data science, Process engineering, Machine learning", "majorSkillsList" : [ "Quantitative finance", "Data science", "Process engineering", "Machine learning" ], "coreResponsibilities" : "Design production processes, Implement production processes, Test production processes, Design process orchestration, Monitor production health, Respond to critical issues, Communicate production issues, Identify computational bottlenecks, Improve run speeds, Collaborate with investment teams, Meet process needs, Evaluate process improvements, Assess data quality, Maintain process repos, Clean code, Construct algorithms, Run algorithms, Validate data sets, Design data loaders, Test data loaders, Perform data analysis, Provide data expertise, Facilitate ML pipelines, Audit ML pipelines, Analyze ML pipelines, Enable accessibility, Clarify data assets, Scrub data, Develop methodologies, Assess data, Analyze data, Respond to vendor data issues, Mitigate vendor data issues, Integrate data, Present findings, Present recommendations", "teamCollaboration" : "Cross-functional teams; Investment teams; Senior members", "projectManagementSkills" : [ "Agile", "Scrum", "JIRA", "Roadmap planning", "Kanban", "PMP" ], "domainKnowledge" : "Quantitative equity investment management; Investment engine; Alpha; Risk; Portfolio optimization; Market implementation; Quantitative model; Portfolios; Data assets; Optimizers; Systematic investment insights; Vendor data", "domainList" : [ "quantitative-equity-investment-management", "investment-engine", "alpha", "risk", "portfolio-optimization", "market-implementation", "quantitative-model", "portfolios", "data-assets", "optimizers", "systematic-investment-insights", "vendor-data" ], "domainSpecificKnowledge" : [ "Quantitative equity investment management", "Investment engine", "Alpha", "Risk", "Portfolio optimization", "Market implementation", "Quantitative model", "Portfolios", "Data assets", "Optimizers", "Systematic investment insights", "Vendor data" ], "toolProficiency" : [ "Dbt Cloud" ], "communicationSkills" : "Executive presentations; Technical documentation; Client meetings", "documentationSkills" : "Technical writing; API documentation; Architecture diagrams", "continuousLearning" : "Mentorship programme; Career development plans", "innovationCreativity" : "Operational innovation; R&D projects; Hackathons; Prototype development; Design thinking", "problemSolvingSkills" : "Root cause analysis; Debugging; Data-driven decision making; Troubleshooting", "outcomesObjectives" : "Accurate trade generation; Timely trade generation", "qualificationsBasic" : "Undergraduate degree in finance, mathematics, statistics, computer science, engineering, or related discipline, SQL proficiency, 5+ years experience", "qualificationsPreferred" : "Completion of CFA, Relevant graduate degree, PhD preferred, Specific ML framework experience, Cloud platform certs", "workSiteFlexibility" : "Flexible", "rawDescription" : "We are looking for a Quantitative Equity Analyst to join our Quantitative Equity Team! We are a high-performance team embedded in a top-performing quant fund that manages over $75 billion in financial assets. We are dedicated to the mission-critical operation of our investment engine—a well-tuned machine responsible for generating key decisions that drive trades and investment insights. Leveraging finance skills and cutting-edge technology, we ensure data quality, continuous process improvement, and operational excellence. As a core member of our team, you'll collaborate with investment experts to tackle challenging analytical problems, be accountable to ensure accurate and timely trade generation, and drive operational innovation. Based in West Coast Vancouver, we value mentorship, collaboration, and growth in a supportive and innovative environment. Join us to make a significant impact on our investment engine and overall success. What You Will Do This is an exciting full-time role for individuals who are passionate about learning the quantitative equity investment management business and excited to tackle a broad range of investment, mathematical, and technology challenges. You will start with a comprehensive training program, learning about various elements of quantitative equity investment management and our investment process. You will then continue to a specialized role utilizing data science and process engineering skillsets to accelerate the Quantitative Equities Team’s various investment functions. Your specialized role may involve building, scaling, managing and/or analyzing our quantitative model, portfolios, data assets and optimizers. You will be supported with coaching and mentorship from senior members of the team. We are creating the conditions for you to grow your career steadily over time. Investment Process Management The team you will be joining is our Investment Process Management (IPM) group within our Quantitative Equities Team. IPM plays a central role in building highly scalable, efficient, and robust process management systems. The processes and infrastructure we maintain are critical in the team’s ability to develop systematic investment insights and generate daily trades to capture these insights in portfolios. The opportunity within the IPM group allows ambitious individuals to drive their career growth within IPM, or across the other functions of the Quantitative Equities Team in Research, Portfolio Construction, or Trading. While we take the approach of tailoring the career path for the individual, we have found our functions to cover two main overarching technical skillsets: Process and Reliability Engineering Design, implement and test production processes to run the alpha and risk, portfolio optimization and market implementation processes. Design robust, high performance and effective process orchestration. Monitor production health and respond to critical issues in a timely manner. Effectively communicate real-time production issues to portfolio managers, traders and researchers. Identify computational bottle necks and improve run speeds in production systems. Collaborate with investment teams to ensure their process needs are being met. Find and evaluate areas for process improvements. Assess and evaluate data quality of production processes. Maintain process repos, clean code and tools within production processes. Data Science Construct and run algorithms to explore and assess data effectively. Validate structured and unstructured data sets for data quality. Design and test data loaders and security matching processes and specifications. Perform data analysis and provide data expertise to support researcher’s projects. Facilitate production machine learning operational pipelines with effective and timely auditing and analysis. Enable accessibility and clarity within our data assets through robust documentation and data scrubbing. Develop robust methodologies for assessing and analyzing data in time critical production environments. Respond to and mitigate vendor data issues effectively in a production setting. Collaborate with cross-functional teams to integrate traditional and alternative data into existing analytical frameworks and decision-making processes. Present findings and recommendations to key stakeholders in a clear, concise, and compelling manner. What You Bring Analytical Mindset – You think critically and creatively and are adept at balancing intuition with statistical validation. Financial Knowledge – You possess a thorough understanding of (or strong desire to learn) key drivers of business success, including financial theory, economic models, and corporate financial statements. Self-Starter – You are motivated and willing to take personal accountability for quality and timeliness of work. Collaborative Approach – You thrive in a collaborative environment and value shared success. You proactively solicit and provide input and excel at communicating complex and technical concepts. Time Management – You have the ability to manage and prioritize multiple ongoing projects and daily responsibilities. Academic Training – At a minimum, an undergraduate degree in finance, mathematics, statistics, computer science, engineering, or related discipline. Completion of CFA or relevant graduate degree is considered an asset. Industry Experience – You have a passion for quantitative finance, equity investment, data science or related fields. Reasons to Grow Your Career with Us Impact – We help create opportunities for you to leverage your personal strengths to make a positive impact on our business. Culture – Collaboration and innovation are deeply rooted in our culture. We enjoy working together and align our passions in pursuit of a shared objective in every project we undertake. Development – We create conditions for success tailored to each employee through internally developed career development plans. Mentorship – We believe that developing great people is the key to great success. You will have opportunities to share, hear and learn about career experiences from peers and senior team members. Work-Life Balance – Vancouver is surrounded by water, mountains, and cherry blossoms. We work hard in our professional lives but also create space to enjoy our personal lives. We welcome applications from candidates with different levels of experience, including interns, new graduates, and experienced professionals. The base salary range for full-time roles is $125,000 – $200,000 annually plus a competitive performance bonus. Compensation will be determined based on experience and qualifications. To apply for this position, please submit your resume, cover letter, and academic transcript. #LI-HYBRID #LI-RC1 CC&L Financial Group is committed to creating a diverse and inclusive environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to gender, ethnicity, religion, sexual orientation or expression, disability, or age.  Your application will be reviewed by a member of the hiring team - AI is not used in the screening, assessment or selection of applications at this time.", "summaryDescription" : "Quantitative Equity Analyst at Connor, Clark & Lunn Investment Management. Skills: Quantitative finance, Data science, Process engineering, Machine learning. Design production processes. Implement production processes", "postedDate" : "2026-06-13T22:20:19.828", "createdAt" : "2026-06-13T22:20:19.828", "lastUpdated" : "2026-06-15T07:14:36.772", "ingestTimestamp" : "2026-06-13T22:20:19.828", "mongoId" : "6a2c7c2274d8ee00a094c65d", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Quantitative analysis", "Statistical validation", "Process management systems", "Algorithmic construction", "Data validation", "Data analysis", "Time series analysis", "Regression", "Classification", "Clustering", "A/B testing", "Causal inference", "Analytical Mindset", "Collaborative Approach", "Time Management", "Quantitative finance", "Data science", "Process engineering", "Machine learning", "Data expertise", "Data quality assessment", "Data scrubbing", "Data integration", "Financial theory", "Economic models", "Corporate financial statements", "Agile", "Scrum", "JIRA", "Roadmap planning", "Kanban", "PMP", "Quantitative equity investment management", "Investment engine", "Alpha", "Risk", "Portfolio optimization", "Market implementation", "Quantitative model", "Portfolios", "Data assets", "Optimizers", "Systematic investment insights", "Vendor data", "CFA", "Dbt Cloud" ], "skillCount" : 46, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Mid", "dataQualityScore" : 0.8888889, "_score" : 650.4106, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c7c2274d8ee00a094c65c", "title" : "Quantitative Equity Analyst", "company" : "Connor, Clark & Lunn Investment Management", "industry" : "FinTech", "salary" : { "min" : 125000.0, "max" : 200000.0, "currency" : "CAD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Vancouver, British Columbia, Canada", "locations" : [ "Vancouver", "British Columbia", "Canada" ], "timestamp" : "2026-06-16T05:04:26.818", "fingerprint" : "e82eebd1482170b061ef2a188b30356b72d4c7ed4e57d20f5bfef9a25d207f62", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/cclim/jobs/4223791009", "externalId" : "4223791009", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Vancouver", "state" : "British Columbia", "country" : "Canada", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "49.2608724,-123.1139520" } ], "locationText" : "Vancouver, British Columbia, Canada", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "remoteFriendly" : false, "rawDescription" : "We are looking for a Quantitative Equity Analyst to join our Quantitative Equity Team! We are a high-performance team embedded in a top-performing quant fund that manages over $75 billion in financial assets. We are dedicated to the mission-critical operation of our investment engine—a well-tuned machine responsible for generating key decisions that drive trades and investment insights. Leveraging finance skills and cutting-edge technology, we ensure data quality, continuous process improvement, and operational excellence. As a core member of our team, you'll collaborate with investment experts to tackle challenging analytical problems, be accountable to ensure accurate and timely trade generation, and drive operational innovation. Based in West Coast Vancouver, we value mentorship, collaboration, and growth in a supportive and innovative environment. Join us to make a significant impact on our investment engine and overall success. What You Will Do This is an exciting full-time role for individuals who are passionate about learning the quantitative equity investment management business and excited to tackle a broad range of investment, mathematical, and technology challenges. You will start with a comprehensive training program, learning about various elements of quantitative equity investment management and our investment process. You will then continue to a specialized role utilizing data science and process engineering skillsets to accelerate the Quantitative Equities Team’s various investment functions. Your specialized role may involve building, scaling, managing and/or analyzing our quantitative model, portfolios, data assets and optimizers. You will be supported with coaching and mentorship from senior members of the team. We are creating the conditions for you to grow your career steadily over time. Investment Process Management The team you will be joining is our Investment Process Management (IPM) group within our Quantitative Equities Team. IPM plays a central role in building highly scalable, efficient, and robust process management systems. The processes and infrastructure we maintain are critical in the team’s ability to develop systematic investment insights and generate daily trades to capture these insights in portfolios. The opportunity within the IPM group allows ambitious individuals to drive their career growth within IPM, or across the other functions of the Quantitative Equities Team in Research, Portfolio Construction, or Trading. While we take the approach of tailoring the career path for the individual, we have found our functions to cover two main overarching technical skillsets: Process and Reliability Engineering Design, implement and test production processes to run the alpha and risk, portfolio optimization and market implementation processes. Design robust, high performance and effective process orchestration. Monitor production health and respond to critical issues in a timely manner. Effectively communicate real-time production issues to portfolio managers, traders and researchers. Identify computational bottle necks and improve run speeds in production systems. Collaborate with investment teams to ensure their process needs are being met. Find and evaluate areas for process improvements. Assess and evaluate data quality of production processes. Maintain process repos, clean code and tools within production processes. Data Science Construct and run algorithms to explore and assess data effectively. Validate structured and unstructured data sets for data quality. Design and test data loaders and security matching processes and specifications. Perform data analysis and provide data expertise to support researcher’s projects. Facilitate production machine learning operational pipelines with effective and timely auditing and analysis. Enable accessibility and clarity within our data assets through robust documentation and data scrubbing. Develop robust methodologies for assessing and analyzing data in time critical production environments. Respond to and mitigate vendor data issues effectively in a production setting. Collaborate with cross-functional teams to integrate traditional and alternative data into existing analytical frameworks and decision-making processes. Present findings and recommendations to key stakeholders in a clear, concise, and compelling manner. Reasons to Grow Your Career with Us Impact – We help create opportunities for you to leverage your personal strengths to make a positive impact on our business. Culture – Collaboration and innovation are deeply rooted in our culture. We enjoy working together and align our passions in pursuit of a shared objective in every project we undertake. Development – We create conditions for success tailored to each employee through internally developed career development plans. Mentorship – We believe that developing great people is the key to great success. You will have opportunities to share, hear and learn about career experiences from peers and senior team members. Work-Life Balance – Vancouver is surrounded by water, mountains, and cherry blossoms. We work hard in our professional lives but also create space to enjoy our personal lives. What You Bring Analytical Mindset – You think critically and creatively and are adept at balancing intuition with statistical validation. Financial Knowledge – You possess a thorough understanding of (or strong desire to learn) key drivers of business success, including financial theory, economic models, and corporate financial statements. Self-Starter – You are motivated and willing to take personal accountability for quality and timeliness of work. Collaborative Approach – You thrive in a collaborative environment and value shared success. You proactively solicit and provide input and excel at communicating complex and technical concepts. Time Management – You have the ability to manage and prioritize multiple ongoing projects and daily responsibilities. Academic Training – At a minimum, an undergraduate degree in finance, mathematics, statistics, computer science, engineering, or related discipline. Completion of CFA or relevant graduate degree is considered an asset. Industry Experience – You have a passion for quantitative finance, equity investment, data science or related fields. We welcome applications from candidates with different levels of experience, including interns, new graduates, and experienced professionals. The base salary range for full-time roles is $125,000 – $200,000 annually plus a competitive performance bonus. Compensation will be determined based on experience and qualifications. To apply for this position, please submit your resume, cover letter, and academic transcript. #LI-HYBRID #LI-RC1 CC&L Financial Group is committed to creating a diverse and inclusive environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to gender, ethnicity, religion, sexual orientation or expression, disability, or age.  Your application will be reviewed by a member of the hiring team - AI is not used in the screening, assessment or selection of applications at this time.", "summaryDescription" : "Quantitative Equity Analyst at Connor, Clark & Lunn Investment Management", "postedDate" : "2026-06-14T21:47:45.754", "createdAt" : "2026-06-14T21:47:45.754", "lastUpdated" : "2026-06-16T05:04:26.818", "ingestTimestamp" : "2026-06-14T21:47:45.754", "mongoId" : "6a2c7c2274d8ee00a094c65c", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Mid", "dataQualityScore" : 0.7777778, "_score" : 646.7613, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Financial Services", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c7c2274d8ee00a094c65a", "title" : "Quantitative Data Analyst", "company" : "Connor, Clark & Lunn Investment Management", "salary" : { "min" : 125000.0, "max" : 200000.0, "currency" : "CAD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Vancouver, British Columbia, Canada", "locations" : [ "Vancouver", "British Columbia", "Canada" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T01:31:13.653", "fingerprint" : "34ff43fdb29565fe9574fc665d34d1166817e7140448eab71542980c12aae3d4", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/cclim/jobs/4223817009", "externalId" : "4223817009", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Vancouver", "state" : "British Columbia", "country" : "Canada", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "49.2608724,-123.1139520" } ], "locationText" : "Vancouver, British Columbia, Canada", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "technicalSkills" : "SQL, Python, R, Scala, Spark, Dbt, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Dbt Cloud, Delta Lake, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, S3, Glue, SageMaker, Athena, GCP, Vertex AI, Azure, Synapse, ML Studio", "professionalSkills" : [ "Data engineering", "ML/AI", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Modelling skills" ], "hardSkillsList" : [ "Statistical analysis", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference" ], "hardSkills" : [ { "name" : "Statistical analysis", "level" : "intermediate" }, { "name" : "Regression", "level" : "intermediate" }, { "name" : "Classification", "level" : "intermediate" }, { "name" : "Clustering", "level" : "intermediate" }, { "name" : "Time-series analysis", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "majorSkills" : "Data science, Data engineering, ML/AI, Business intelligence", "majorSkillsList" : [ "Data science", "Data engineering", "ML/AI", "Business intelligence" ], "coreResponsibilities" : "Develop and implement data pipelines, Build and maintain data models, Design and deploy machine learning models, Create and maintain BI dashboards, Perform statistical analysis, Collaborate with stakeholders", "teamCollaboration" : "Cross-functional teams; Stakeholders", "toolProficiency" : [ "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy" ], "qualificationsBasic" : "SQL proficiency, 5+ years experience", "qualificationsPreferred" : "PhD preferred, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified certification, Dbt Certified certification", "remoteFriendly" : false, "rawDescription" : "We are looking for a Quantitative Data Analyst to join our Quantitative Equity Team! We are a high-performance team embedded in a top-performing quant fund that manages over $75 billion in financial assets. We are dedicated to the mission-critical operation of our investment engine—a well-tuned machine responsible for generating key decisions that drive trades and investment insights. Leveraging data analytics, finance knowledge and cutting-edge technology, we aim to ensure that new and useful data products are continuously ready for research. Do you love the idea of integrating large proprietary data sources into valuable applications? Are you a wizard at transforming ‘messy reality’ into high quality data assets? As a core member of our team, you will collaborate with investment and data experts to tackle challenging problems, and to continuously expand our capabilities in data. Based on the west coast in Vancouver, we value mentorship, collaboration, and growth in a supportive and innovative environment. Join us to make a significant impact on our investment outcomes and overall success. What You Will Do This is an exciting full-time role for individuals who are enthusiastic about learning the quantitative equity investment management business and excited to tackle a broad range of data, investment, and technology challenges. You will start with a comprehensive training program, learning about various elements of quantitative equity investment management and our investment process. You will then continue to a specialized role utilizing data analytics and data science skillsets to enable the Quantitative Equity Team’s research. Your role will involve identifying and assessing brand new data, data exploration, and proposing robust ways to integrate data products from many sources. You will be supported with coaching and mentorship from senior members of the team, and we will create the conditions for you to grow your career steadily over time. This is an opportunity for ambitious individuals to drive their career growth in data. While we take the approach of tailoring the career path to individual strengths, we expect successful candidates for this role to develop excellence in the following tasks: Create processes to assess, explore, and link billions of data points. Test structured and unstructured data sets for data quality and reliability. Assess new data opportunities for quality and usefulness. Evaluate your data solutions for sensibility, accuracy, and bias. Collaborate with quantitative researchers – support alpha projects with your data expertise. Collaborate with technology specialists – help trade off application performance and operational feasibility. Support production deployments of your work to ensure long-term reliability. Enable clarity of and access to your work through robust documentation and exposition. Present findings and recommendations to key stakeholders in a clear, concise, and compelling manner. What You Bring Analytical Mindset – You think critically and creatively and are adept at balancing intuition with statistical validation. Financial Knowledge – Desire to acquire the financial context needed to understand your stakeholders and make data decisions with impact. Self-Starter – You are motivated and willing to take personal accountability for quality and timeliness of work. Collaborative Approach – You thrive in a collaborative environment and value shared success. You proactively solicit and provide input and excel at communicating complex and technical concepts. Time Management – You are able to manage and prioritize multiple ongoing projects. Academic Training – At a minimum, an undergraduate degree in finance, mathematics, statistics, computer science, engineering, or related discipline. Completion of a relevant graduate degree is considered an asset. We welcome applications from candidates with different levels of experience, including interns, new graduates, and experienced professionals. The base salary range for full-time roles is $125,000 – $200,000 annually plus a competitive performance bonus. Compensation will be determined based on experience and qualifications. To apply for this position, please submit your resume, cover letter and academic transcripts. #LI-HYBRID #LI-RC1 CC&L Financial Group is committed to creating a diverse and inclusive environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to gender, ethnicity, religion, sexual orientation or expression, disability, or age.  Your application will be reviewed by a member of the hiring team - AI is not used in the screening, assessment or selection of applications at this time.", "summaryDescription" : "Quantitative Data Analyst at Connor, Clark & Lunn Investment Management. Skills: Data science, Data engineering, ML/AI, Business intelligence. Develop and implement data pipelines. Build and maintain data models", "postedDate" : "2026-06-14T20:05:45.793", "createdAt" : "2026-06-14T20:05:45.793", "lastUpdated" : "2026-06-16T01:31:13.653", "ingestTimestamp" : "2026-06-14T20:05:45.793", "mongoId" : "6a2c7c2274d8ee00a094c65a", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Statistical analysis", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference", "Data science", "Data engineering", "ML/AI", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Modelling skills", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy" ], "skillCount" : 25, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Mid", "dataQualityScore" : 0.8888889, "_score" : 645.63824, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a305a08f292fd229cf4ca01", "title" : "Shariah Risk Associate", "industry" : "Risk", "salary" : { "min" : 750000.0, "max" : 1200000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an entry-level Shariah Risk Associate in Mumbai, India, adjusted for the FinTech industry." }, "location" : "Mumbai", "locations" : [ "Mumbai" ], "timestamp" : "2026-06-16T15:17:40.858", "fingerprint" : "cf5009ce7bda801981ef7acacaeb62f02e3709a50b5bf4192a40091cfab27c94", "source" : "lever", "language" : "en", "applyUrl" : "https://jobs.lever.co/wahed.com/79381338-b778-4ab6-a347-d330490fcb14/apply", "externalId" : "79381338-b778-4ab6-a347-d330490fcb14", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Mumbai", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "19.0549990,72.8692035" } ], "locationText" : "Mumbai, India", "employmentType" : "FULL_TIME", "minimumEducation" : "Undergraduate", "coreResponsibilities" : "Review internal documents, Review contracts, Review product materials, Support Shariah compliance monitoring, Maintain approval records, Maintain trackers, Maintain audit documentation, Conduct basic research, Prepare summaries, Prepare internal reports, Prepare presentations, Support Shariah team, Respond to internal queries, Respond to risk reviews, Respond to audit requirements, Maintain organized documentation, Maintain version control, Maintain structured archives", "domainKnowledge" : "Shariah perspective; Shariah compliance; Shariah rulings; AAOIFI standards; Islamic finance practices; Islamic commercial jurisprudence; Fiqh al-Mu‘amalat; Islamic Studies; Shariah; Islamic Finance", "domainList" : [ "shariah-perspective", "shariah-compliance", "shariah-rulings", "aaoifi-standards", "islamic-finance-practices", "islamic-commercial-jurisprudence", "fiqh-al-mu-amalat", "islamic-studies", "shariah", "islamic-finance" ], "domainSpecificKnowledge" : [ "Shariah perspective", "Shariah compliance", "Shariah rulings", "AAOIFI standards", "Islamic finance practices", "Islamic commercial jurisprudence", "Fiqh al-Mu‘amalat", "Islamic Studies", "Shariah", "Islamic Finance" ], "communicationSkills" : "Written communication", "documentationSkills" : "Formal documentation", "qualificationsBasic" : "Undergraduate or postgraduate student, Basic understanding of Islamic jurisprudence, Comfortable working with spreadsheets, Comfortable working with documents, Comfortable working with internal systems", "qualificationsPreferred" : "Arabic language advantage", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "## Job Description Assist in reviewing internal documents, contracts, and product materials from a Shariah perspective. Support Shariah compliance monitoring activities, including maintaining approval records, trackers, and audit documentation. Conduct basic research on Shariah rulings, AAOIFI standards, and contemporary Islamic finance practices. Help prepare summaries, internal reports, and presentations for Shariah reviews and training sessions. Support the Shariah team in responding to internal queries, risk reviews, and audit requirements. Maintain organized documentation, version control, and structured archives for Shariah-related materials. ## Job Specification Undergraduate or postgraduate student in Islamic Studies, Shariah, Islamic Finance, or a related field. Basic understanding of Islamic commercial jurisprudence (Fiqh al-Mu‘amalat). Strong attention to detail and ability to work with formal documentation. Good written communication skills in English (Arabic is an advantage). Comfortable working with spreadsheets, documents, and internal systems.", "summaryDescription" : "Shariah Risk Associate. Review internal documents. Review contracts", "postedDate" : "2026-06-15T09:00:35.549", "createdAt" : "2026-06-15T09:00:35.549", "lastUpdated" : "2026-06-16T15:17:40.858", "ingestTimestamp" : "2026-06-16T03:23:06.526", "mongoId" : "6a305a08f292fd229cf4ca01", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Shariah perspective", "Shariah compliance", "Shariah rulings", "AAOIFI standards", "Islamic finance practices", "Islamic commercial jurisprudence", "Fiqh al-Mu‘amalat", "Islamic Studies", "Shariah", "Islamic Finance" ], "skillCount" : 10, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Entry", "dataQualityScore" : 0.7777778, "_score" : 640.4021, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.92 }, { "id" : "6a2c6bb474d8ee00a09141c4", "title" : "Experienced Quantitative Researcher", "company" : "Quantbox Research", "industry" : "FinTech", "salary" : { "min" : 110000.0, "max" : 160000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Senior Quantitative Researcher in Amsterdam, Netherlands, adjusted for FinTech industry and company size." }, "location" : "Amsterdam, North Holland, Netherlands", "locations" : [ "Amsterdam", "North Holland", "Netherlands", "Bengaluru", "Karnataka", "India", "Hong Kong", "Singapore", "Central", "Singapore" ], "timestamp" : "2026-06-15T10:45:08.126", "fingerprint" : "aaf7c88cdb754587e85c91d6839152b00431aeb118836edaf69362e17e8356d8", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/quantboxresearchpte/jobs/4001033101", "externalId" : "4001033101", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Amsterdam", "state" : "North Holland", "country" : "Netherlands", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "52.3730796,4.8924534" } ], "locationText" : "Amsterdam, North Holland, Netherlands", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 2, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, R, Kdb+, C++", "professionalSkills" : [ "Market making", "Systematic alpha research" ], "hardSkillsList" : [ "Quantitative research", "Statistical analysis" ], "hardSkills" : [ { "name" : "Quantitative research", "level" : "intermediate" }, { "name" : "Statistical analysis", "level" : "intermediate" } ], "majorSkills" : "High frequency trading, Quantitative research", "majorSkillsList" : [ "High frequency trading", "Quantitative research" ], "coreResponsibilities" : "Research systematic HFT market making strategies, Develop systematic HFT market making strategies, Leverage existing technology, Leverage existing infrastructure", "teamCollaboration" : "Small collaborative environment; Experienced traders; Experienced developers", "domainKnowledge" : "Proprietary trading; Electronic market making; Asset classes", "domainList" : [ "proprietary-trading", "electronic-market-making", "asset-classes" ], "domainSpecificKnowledge" : [ "Proprietary trading", "Electronic market making", "Asset classes" ], "innovationCreativity" : "Innovate; New technologies; New ideas", "qualificationsBasic" : "Deep experience in high frequency trading, Live high frequency trading experience for at least 2 years, PnL track record with excellent Sharpe ratios", "qualificationsPreferred" : "Degree from top tier college or university a plus", "workSiteFlexibility" : "Flexible", "rawDescription" : "Quantbox is a technology-driven Proprietary trading firm that specializes in systematic alpha research and electronic market-making on various exchanges. We trade across a multitude of asset classes and trading venues with significant market share and are looking for experienced Quantitative Researchers to join our team. As a Quantitative Researcher, you will be working with experienced traders and developers to research and develop new systematic HFT market making strategies leveraging our existing technology and infrastructure. Quantbox encourages Bachelor’s, Master’s and PhD students in computer science, mathematics and related fields to apply. Additional requirements include: Deep experience in high frequency trading Live high frequency trading experience for at least 2 years. PnL track record with excellent Sharpe ratios. Taking pride in building solutions using Python, R, kdb+ or C++ Desire to work in a small collaborative environment Degree from top tier college or university a plus A passion for new technologies and ideas Strong communication skills Quantbox is a place of friends and colleagues, where people convert their passion into action. We believe in togetherness that brings out the best in ourselves and our Company. Our open and casual work culture gives you the space to innovate and deliver. Everyone on the team is approachable. Employee remuneration packages are reviewed regularly to ensure that they remain competitive. In recognition of our employees’ contributions and performance, for full time permanent roles we provide: Competitive compensation 4 Weeks of paid vacation Medical insurance International team outing Quantbox is an equal opportunities employer.", "summaryDescription" : "Experienced Quantitative Researcher at Quantbox Research. Skills: High frequency trading, Quantitative research. Research systematic HFT market making strategies. Develop systematic HFT market making strategies", "postedDate" : "2026-06-14T08:01:11.800", "createdAt" : "2026-06-14T08:01:11.800", "lastUpdated" : "2026-06-15T10:45:08.126", "ingestTimestamp" : "2026-06-14T08:01:11.800", "mongoId" : "6a2c6bb474d8ee00a09141c4", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Quantitative research", "Statistical analysis", "High frequency trading", "Market making", "Systematic alpha research", "Proprietary trading", "Electronic market making", "Asset classes" ], "skillCount" : 8, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 1.0, "_score" : 636.8998, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a3079f5f292fd229c0365f0", "title" : "Quantitative Researcher - Macro Assets", "company" : "Man Group", "salary" : { "min" : 75000.0, "max" : 110000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Junior Quantitative Researcher in London, adjusted for the financial services industry and a large company size." }, "location" : "London", "locations" : [ "London" ], "timestamp" : "2026-06-16T12:04:26.270", "fingerprint" : "2de1383a9597a3c8edb8df0cca380508a9f66fddb2e459b62ed31e2bf9082317", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/mangroup/jobs/4880305101", "externalId" : "4880305101", "industryFunction" : { }, "structuredLocations" : [ { "city" : "London", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "51.5074456,-0.1277653" } ], "locationText" : "London, United Kingdom", "remoteFriendly" : true, "rawDescription" : "About Man Group Man Group is a global alternative investment management firm focused on pursuing outperformance for sophisticated clients via our Systematic, Discretionary and Solutions offerings. Powered by talent and advanced technology, our single and multi-manager investment strategies are underpinned by deep research and span public and private markets, across all major asset classes, with a significant focus on alternatives. Man Group takes a partnership approach to working with clients, establishing deep connections and creating tailored solutions to meet their investment goals and those of the millions of retirees and savers they represent. Headquartered in London, we manage $227.6 billion* and operate across multiple offices globally. Man Group plc is listed on the London Stock Exchange under the ticker EMG.LN and is a constituent of the FTSE 250 Index. Further information can be found at www.man.com * As at 31 December 2025 The Team AHL Global Macro is the business unit responsible for global macro strategies across all asset classes. The team trade all markets, from liquid to alternative universe, with strategies spanning multiple holding periods. This role sits within the AHL Global Trend And Volatility sector. This role's research mission is to model the behaviour of global macro assets and identify alpha signals, with a particular focus on understanding and modelling what drives trends in macro assets and the timing of this style. The Role You will conduct original alpha research on global macro assets, building and testing predictive signals that inform live trading strategies. You will work across the full research lifecycle — from hypothesis generation and statistical modelling through to implementation and ongoing performance analysis — with direct exposure to live strategy management. Day-to-day you will: Research and develop alpha signals across global macro asset classes, with a focus on trend timing and directional strategies Model the dynamics of macro assets (rates, FX, equities, commodities) to identify exploitable patterns Design and evaluate predictive signals using rigorous statistical and quantitative methods Contribute to portfolio construction and risk analysis across the sector's strategies Monitor live strategy performance and translate observations back into research hypotheses Collaborate with researchers across AHL Global Macro and contribute to the broader research agenda Technology and Business Skills: 2+ years of experience researching alpha signals across macro assets Solid grounding in statistical and mathematical modelling; able to choose the right tool for the right problem Strong Python skills; comfortable working with large financial datasets Understanding of portfolio construction and risk analysis Familiarity with transaction costs and their impact on signal design is a plus Personal Attributes Strong academic record with a degree in a quantitative discipline — Mathematics, Statistics, Physics, Computer Science, Engineering or Economics from a leading university; a PhD or Master's is advantageous Intellectually curious with a genuine interest in financial markets and the macro forces that move them Hands-on and rigorous: you enjoy following an idea all the way from intuition to tested, implemented signal Self-organised with the ability to manage multiple research threads in parallel Clear communicator: able to present quantitative findings concisely and engage constructively with alternative views Collaborative; comfortable working closely with researchers, technologists and portfolio managers Inclusion, Work-Life Balance and Benefits at Man Group You'll thrive in our working environment that champions equality of opportunity. Your unique perspective will contribute to our success, joining a workplace where inclusion is fundamental and deeply embedded in our culture and values. Through our external and internal initiatives, partnerships and programmes, you'll find opportunities to grow, develop your talents, and help foster an inclusive environment for all across our firm and industry. Learn more at www.man.com/diversity. You'll have opportunities to make a difference through our charitable and global initiatives, while advancing your career through professional development, and with flexible working arrangements available too. Like all our people, you'll receive two annual 'Mankind' days of paid leave for community volunteering. Our comprehensive benefits package includes competitive holiday entitlements, pension/401k, life and long-term disability coverage, group sick pay, enhanced parental leave and long-service leave. Depending on your location, you may also enjoy additional benefits such as private medical coverage, discounted gym membership options and pet insurance. Equal Employment Opportunity Policy Man Group provides equal employment opportunities to all applicants and all employees without regard to race, color, creed, national origin, ancestry, religion, disability, sex, gender identity and expression, marital status, sexual orientation, military or veteran status, age or any other legally protected category or status in accordance with applicable federal, state and local laws. Man Group is a Disability Confident Committed employer; if you require help or information on reasonable adjustments as you apply for roles with us, please contact TalentAcquisition@man.com.", "summaryDescription" : "Quantitative Researcher - Macro Assets at Man Group", "postedDate" : "2026-06-16T01:17:44.909", "createdAt" : "2026-06-16T01:17:44.909", "lastUpdated" : "2026-06-16T12:04:26.270", "ingestTimestamp" : "2026-06-16T01:17:44.909", "mongoId" : "6a3079f5f292fd229c0365f0", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "75k-100k", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Junior", "dataQualityScore" : 0.6666667, "_score" : 628.20715, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Financial Services", "llmIndustryConfidence" : 0.98 }, { "id" : "6a3079f5f292fd229c0365ed", "title" : "Quantitative Portfolio Implementation Analyst", "company" : "Man Group", "industry" : "FinTech", "salary" : { "min" : 135000.0, "max" : 195000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-level Quantitative Portfolio Implementation Analyst in Massachusetts, USA, with adjustments for the Financial Services industry and a large company size." }, "location" : "Massachusetts", "locations" : [ "Massachusetts" ], "timestamp" : "2026-06-16T11:33:04.367", "fingerprint" : "0648696c0c236da2f89e083195439ddda04f48311af5fce247e6693f82b0c297", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/mangroup/jobs/4890008101", "externalId" : "4890008101", "industryFunction" : { }, "structuredLocations" : [ { "state" : "Massachusetts", "country" : "United States", "continent" : "na", "workMode" : "onsite" } ], "locationText" : "Massachusetts, United States", "rawDescription" : "About Man Group Man Group is a global alternative investment management firm focused on pursuing outperformance for sophisticated clients via our Systematic, Discretionary and Solutions offerings. Powered by talent and advanced technology, our single and multi-manager investment strategies are underpinned by deep research and span public and private markets, across all major asset classes, with a significant focus on alternatives. Man Group takes a partnership approach to working with clients, establishing deep connections and creating tailored solutions to meet their investment goals and those of the millions of retirees and savers they represent. Headquartered in London, we manage $227.6 billion* and operate across multiple offices globally. Man Group plc is listed on the London Stock Exchange under the ticker EMG.LN and is a constituent of the FTSE 250 Index. Further information can be found at www.man.com * As at 31 December 2025 THE TEAM Man Group's quantitative investment engines, AHL and Numeric, are aligning under Systematic (USD ~138bn AUM). As part of this integration, we are expanding our Investment and Data Implementation (IDI) team, which has supported AHL for many years, into a new Boston-based team supporting the Man Numeric business. The global IDI team spans Hong Kong, Sofia, London and now Boston. The Boston team is responsible for implementing all new business and portfolios (funds, Separately Managed Accounts (SMAs), and investment strategies), maintaining the integrity of systematic models, and steering the long-term development of our trading initiatives. Our mission is to ensure every quantitative strategy is implemented with precision and aligned with its investment objectives, from initial research idea through to the last trade. Though Boston-based and focused primarily on Man Numeric’s content, as part of Systematic, you will be part of a connected global network, sharing tooling, codebase, and implementation capabilities across all four locations. The problems the team solves are diverse, complex, and high-impact. The team is the primary responder when production issues halt the investment managers, requiring rapid diagnosis and resolution without introducing new risks. The team are the operational architects who translate a researcher’s ideal strategy or portfolio into a robust, scalable solution, balancing speed, resilience, and business logic. The team also works closely with other areas such as Portfolio Management and Trading to explain why an algorithm and portfolio optimizer generated specific trades. Finally, we partner with technologists to help design trading architecture that is automated, scalable, and transparent enough for manual intervention when necessary. This role offers exceptional exposure. Man Group's flat structure means your work is widely visible across the group, you will be working with portfolio managers, quantitative researchers, product structuring specialists, and traders, with the opportunity and expectation to contribute, propose solutions, and make decisions regardless of seniority. You’ll be supported throughout and as you build confidence, you will represent the global IDI team on cross-departmental working groups and present findings directly to senior management. THE ROLE We are seeking a highly motivated professional to bridge quantitative research, portfolio management, technology, trading, and middle the ability to interact confidently with portfolio managers and domain experts Dependable judgment under pressure A relentless focus on delivering value to the business and improving implementation processes Advantageous: High level understanding of quantitative investment processes and portfolio construction Experience with portfolio management and/or trading systems, along with proficiency in data analysis and process automation Experience delivering or steering complex projects, such as fund or Separately Managed Account (SMA) launches Commercial experience or a strong interest in using AI tools to drive workflow efficiency and business insights Generalist experience and exposures within buy-side systematic investment (Implementation, Front Office, Middle Office or Trade Operations) Ability to use SQL and an object-oriented language (preferably Python) to investigate data and prototype solutions Proficiency in data reasoning techniques and relevant libraries (e.g., Pandas) The anticipated based salary range for this position is listed below. Compensation packages would also include benefits and a discretionary bonus. This is the base salary range that the Company believes it will pay for this position at the time of this posting based on the location and requirements of the position as well as the skills, qualifications, and experience of the applicant. The Firm reserves the right to modify this pay range at any time. US Pay Range $85,000—$100,000 USD Inclusion, Work-Life Balance and Benefits at Man Group You'll thrive in our working environment that champions equality of opportunity. Your unique perspective will contribute to our success, joining a workplace where inclusion is fundamental and deeply embedded in our culture and values. Through our external and internal initiatives, partnerships and programmes, you'll find opportunities to grow, develop your talents, and help foster an inclusive environment for all across our firm and industry. Learn more at www.man.com/diversity. You'll have opportunities to make a difference through our charitable and global initiatives, while advancing your career through professional development, and with flexible working arrangements available too. Like all our people, you'll receive two annual 'Mankind' days of paid leave for community volunteering. Our comprehensive benefits package includes competitive holiday entitlements, pension/401k, life and long-term disability coverage, group sick pay, enhanced parental leave and long-service leave. Depending on your location, you may also enjoy additional benefits such as private medical coverage, discounted gym membership options and pet insurance. Equal Employment Opportunity Policy Man Group provides equal employment opportunities to all applicants and all employees without regard to race, color, creed, national origin, ancestry, religion, disability, sex, gender identity and expression, marital status, sexual orientation, military or veteran status, age or any other legally protected category or status in accordance with applicable federal, state and local laws. Man Group is a Disability Confident Committed employer; if you require help or information on reasonable adjustments as you apply for roles with us, please contact TalentAcquisition@man.com.", "summaryDescription" : "Quantitative Portfolio Implementation Analyst at Man Group", "postedDate" : "2026-06-16T01:16:52.116", "createdAt" : "2026-06-16T01:16:52.116", "lastUpdated" : "2026-06-16T11:33:04.367", "ingestTimestamp" : "2026-06-16T01:16:52.116", "mongoId" : "6a3079f5f292fd229c0365ed", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 135000, "salaryAnnualMax" : 195000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Mid", "dataQualityScore" : 0.6666667, "_score" : 628.1861, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Financial Services", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c7c2274d8ee00a094c65e", "title" : "Quantitative Research Analyst", "company" : "Connor, Clark & Lunn Investment Management", "industry" : "FinTech", "salary" : { "min" : 125000.0, "max" : 200000.0, "currency" : "CAD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Vancouver, British Columbia, Canada", "locations" : [ "Vancouver", "British Columbia", "Canada" ], "timestamp" : "2026-06-15T05:00:42.980", "fingerprint" : "35014933c5ef34b909fb994d950ec77ba17e336901e5e3b808228540df251bce", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/cclim/jobs/4223730009", "externalId" : "4223730009", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Vancouver", "state" : "British Columbia", "country" : "Canada", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "49.2608724,-123.1139520" } ], "locationText" : "Vancouver, British Columbia, Canada", "minimumEducation" : "Bachelor's", "technicalSkills" : "Data science, Statistics", "professionalSkills" : [ "Securities valuation", "Quantitative research", "Investment insights" ], "hardSkillsList" : [ "Algorithmic strategies", "Predictive modeling" ], "hardSkills" : [ { "name" : "Algorithmic strategies", "level" : "intermediate" }, { "name" : "Predictive modeling", "level" : "intermediate" } ], "majorSkills" : "Quantitative research, Data science, Finance", "majorSkillsList" : [ "Quantitative research", "Data science", "Finance" ], "coreResponsibilities" : "Research and development of new investment models, Generate ideas for new investment insights, Apply skills and techniques in finance, Apply skills and techniques in data science, Apply skills and techniques in statistics, Collaborate with technology teams, Collaborate with portfolio management teams, Collaborate with investment process teams, Deliver exceptional investment performance", "teamCollaboration" : "Quantitative Equity team; Quantitative research team; Technology teams; Portfolio management teams; Investment process teams", "domainKnowledge" : "Financial markets; Algorithmic investment strategies; Securities valuation", "domainList" : [ "financial-markets", "algorithmic-investment-strategies", "securities-valuation" ], "domainSpecificKnowledge" : [ "Financial markets", "Algorithmic investment strategies", "Securities valuation" ], "toolProficiency" : [ "Bloomberg Terminal" ], "communicationSkills" : "Communicating complex concepts", "problemSolvingSkills" : "Analytical Mindset", "outcomesObjectives" : "Deliver top tier performance", "qualificationsBasic" : "Undergraduate degree in finance, Undergraduate degree in mathematics, Undergraduate degree in statistics, Undergraduate degree in computer science", "qualificationsPreferred" : "Graduate level studies", "rawDescription" : "We are looking for a Quantitative Research Analyst to join our fast-paced and entrepreneurial Quantitative Equity team! We are a high-performance team embedded in a top-performing quant fund that manages over $75 billion in financial assets. We combine leading edge quantitative research with state-of-the-art technology to develop our unique algorithmic investment strategies. A culture of innovation, growth and success through collaboration has enabled us to deliver top tier performance for over two decades. What You Will Do As a member of the quantitative research team, you will help tackle a broad array of challenges at the Intersection of finance, data science, and technology. We seek to identify novel predictors of business outcomes and model complex inefficiencies in constantly evolving financial markets. Our focus is on developing cutting edge and uniquely powerful investment insights. This is an exciting role for an individual who is passionate about quantitative research and wants to apply a disciplined and scientific approach to investing. You will work with key decision makers on the team and have a broad range of responsibilities, including: Research and development of new investment models Generating ideas for new investment insights Apply a variety of skills and techniques in finance, data science and statistics Collaborate with our technology, portfolio management and investment process teams to deliver exceptional investment performance What You Bring Domain Expertise – You have a deep understanding of the drivers of business success, securities valuation, and markets. You can effectively apply both creativity and discipline to sourcing and evaluating novel data sets that are useful for predicting the performance of companies and securities. Analytical Mindset – You have experience with producing rigorous quantitative research, particularly in finance, and are adept at balancing intuition with statistical validation. Academic Training – At a minimum, an undergraduate degree in finance, mathematics, statistics, computer science or related discipline. Graduate level studies are valuable in this role. Exceptional achievements and recognition (e.g., research or awards) are helpful in demonstrating your abilities. Collaborative Approach – You thrive in a collaborative environment and value shared success. You proactively solicit and provide input and excel at communicating complex and technical concepts. We welcome applications from candidates with different levels of experience, including interns, new graduates, and experienced professionals. The annual base salary for this position is $125,000 - $200,000 for new graduates. Our compensation and benefits package includes substantial variable compensation in the form of a year-end bonus, RRSP contribution matching, health benefits, and family building benefits. Compensation will be determined based on experience and qualifications. To apply for this position, please submit your resume, cover letter and transcript. Please note, this posting is specifically for the quantitative research group and experience in academic research is usually preferred. #LI-HYBRID #LI-RC1 CC&L Financial Group is committed to creating a diverse and inclusive environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to gender, ethnicity, religion, sexual orientation or expression, disability, or age.  Your application will be reviewed by a member of the hiring team - AI is not used in the screening, assessment or selection of applications at this time.", "summaryDescription" : "Quantitative Research Analyst at Connor, Clark & Lunn Investment Management. Skills: Quantitative research, Data science, Finance. Research and development of new investment models. Generate ideas for new investment insights", "postedDate" : "2026-06-14T04:00:17.587", "createdAt" : "2026-06-14T04:00:17.587", "lastUpdated" : "2026-06-15T05:00:42.980", "ingestTimestamp" : "2026-06-14T04:00:17.587", "mongoId" : "6a2c7c2274d8ee00a094c65e", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Algorithmic strategies", "Predictive modeling", "Quantitative research", "Data science", "Finance", "Securities valuation", "Investment insights", "Financial markets", "Algorithmic investment strategies", "Bloomberg Terminal" ], "skillCount" : 10, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Entry", "dataQualityScore" : 0.7777778, "_score" : 618.77295, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Financial Services", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6bb474d8ee00a09141c7", "title" : "Junior Quantitative Researcher", "company" : "Quantbox Research", "industry" : "FinTech", "salary" : { "min" : 45000.0, "max" : 65000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Junior Quantitative Researcher in Amsterdam, Netherlands, adjusted for entry-level experience and the FinTech industry." }, "location" : "Amsterdam, North Holland, Netherlands", "locations" : [ "Amsterdam", "North Holland", "Netherlands" ], "timestamp" : "2026-06-15T08:51:38.012", "fingerprint" : "66f88c066458580e20fe8613a3abdeb66e476c31f8ceaff19236d420e6f6f77e", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/quantboxresearchpte/jobs/4081386101", "externalId" : "4081386101", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Amsterdam", "state" : "North Holland", "country" : "Netherlands", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "52.3730796,4.8924534" } ], "locationText" : "Amsterdam, North Holland, Netherlands", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 0, "experienceMaxYears" : 2, "experienceLevel" : "Entry", "technicalSkills" : "Python, C++, R", "coreResponsibilities" : "Build and improve models", "problemSolvingSkills" : "Creative approach", "qualificationsBasic" : "Bachelor's degree, Python programming, C++ programming, R programming", "qualificationsPreferred" : "PhD", "workSiteFlexibility" : "Onsite", "rawDescription" : "Quantbox is a technology-driven Proprietary trading firm that specializes in systematic alpha research and electronic market-making on various exchanges. We trade across a multitude of asset classes and trading venues with significant market share. We are looking to appoint a Junior Quantitative Researcher/Trader. What you’ll need: You possess a bachelor's degree / Phd in mathematics, computer science, statistics, physics, or a related field Ability to think independently and use creative approach in problem solving Familiarity with python, C++, R programming languages You will be responsible for building and improving the models that keeps us competitive in the market. You will work alongside the traders, software developers and our engineering scientist, you would learn, research, improve, test, build our trading algorithms to increase trading profitability. A typical day involves applying rigorous scientific method, machine learning techniques to a vast array of datasets in order to create insights on how the market behave. Quantbox is an equal opportunity employer. Quantbox is a place of friends and colleagues, where people convert their passion into action. We believe in togetherness that brings out the best in ourselves and our Company. Our open and casual work culture gives you the space to innovate and deliver. Everyone on the team is approachable. Employee remuneration packages are reviewed regularly to ensure that they remain competitive. In recognition of our employees’ contributions and performance, for full time permanent roles we provide: Competitive compensation 4 Weeks of paid vacation Medical insurance International team outing Quantbox is an equal opportunities employer.", "summaryDescription" : "Junior Quantitative Researcher at Quantbox Research. Build and improve models", "postedDate" : "2026-06-14T02:53:47.403", "createdAt" : "2026-06-14T02:53:47.403", "lastUpdated" : "2026-06-15T08:51:38.012", "ingestTimestamp" : "2026-06-14T02:53:47.403", "mongoId" : "6a2c6bb474d8ee00a09141c7", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "30k-50k", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Junior", "dataQualityScore" : 0.8888889, "_score" : 618.56116, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c68ca74d8ee00a0904c4f", "title" : "Senior Quantitative Developer", "company" : "TradingHub", "industry" : "Analytics & Data", "salary" : { "min" : 150000.0, "max" : 250000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Quantitative Developer in London, adjusted for executive seniority in the FinTech industry." }, "location" : "London", "locations" : [ "London" ], "timestamp" : "2026-06-15T08:38:53.289", "fingerprint" : "068a8da09ba8516fd5c1e58bc9169e4586a3cf6bef4177590344ca509e7ab9ab", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/tradinghub/36fd290f-9568-4290-9951-ab73a11d8cbe/application", "externalId" : "36fd290f-9568-4290-9951-ab73a11d8cbe", "industryFunction" : { }, "structuredLocations" : [ { "city" : "London", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "51.5074456,-0.1277653" } ], "locationText" : "London, United Kingdom", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "C#, Python, SQL, Postgres", "professionalSkills" : [ "Pricing models", "Financial pricing", "Risk algorithms", "Securities data analysis", "Market dynamics research", "Model validation" ], "hardSkillsList" : [ "Mathematical analysis", "Financial modeling", "Risk assessment", "Database management" ], "hardSkills" : [ { "name" : "Mathematical analysis", "level" : "intermediate" }, { "name" : "Financial modeling", "level" : "intermediate" }, { "name" : "Risk assessment", "level" : "intermediate" }, { "name" : "Database management", "level" : "intermediate" } ], "majorSkills" : "Quantitative development, Financial markets, Software productionisation", "majorSkillsList" : [ "Quantitative development", "Financial markets", "Software productionisation" ], "coreResponsibilities" : "Develop financial pricing libraries, Develop calculators, Develop risk algorithms, Develop pricing algorithms, Analyze securities data, Produce securities data, Research market dynamics, Prototype proprietary models, Test proprietary models, Validate proprietary models, Support junior team members, Coach junior team members", "teamCollaboration" : "Coaching junior members; Working with experts", "projectManagementSkills" : [ "Prioritisation" ], "domainKnowledge" : "Financial markets; Market manipulation; Asset classes; Fixed-income risk; Derivatives; Options; Swaps; Futures", "domainList" : [ "financial-markets", "market-manipulation", "asset-classes", "fixed-income-risk", "derivatives", "options", "swaps", "futures" ], "domainSpecificKnowledge" : [ "Financial markets", "Market manipulation", "Asset classes", "Fixed-income risk", "Derivatives", "Options", "Swaps", "Futures" ], "continuousLearning" : "Study leave", "innovationCreativity" : "Innovation; R&D", "problemSolvingSkills" : "Mathematical skills; Analytical skills", "outcomesObjectives" : "Ensure product capabilities ahead of competitors", "qualificationsBasic" : "Financial markets experience, Proficiency with C#, Proficiency with Python, Exceptional mathematical skills, Exceptional analytical skills, Understanding of market risk, Knowledge of derivatives, Knowledge of database technologies, Deliver projects to deadlines, Excellent prioritisation skills", "qualificationsPreferred" : "Experience within an investment bank, Experience within a pricing-related firm, Understanding of fixed-income risk", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "Compensation: Competitive (Financial Services) About TradingHub Founded in 2010, TradingHub delivers uniquely intelligent trade surveillance software to world leading financial institutions. Developed by market professionals, our solutions use sophisticated modelling techniques to detect single and cross-product market manipulation. With a team of over 150 experts worldwide, TradingHub combines global reach with deep markets expertise to help our customers mitigate financial, regulatory, and reputational risk. The Role We are seeking a Senior Quantitative Developer (VP) to take a leading role in designing, building and validating our pricing models. This includes creating financial pricing libraries for multiple asset classes, calculators and risk algorithms. The successful candidate will combine excellent mathematical skills with proven experience in financial markets and the ability to productionise high-quality software. The capacity to put yourself in the eyes of a trader will be very useful as we continue to ensure our product’s capabilities are ahead of competitors in the market. Responsibilities: - Development of financial pricing libraries, calculators as well as risk/pricing-related algorithms - Using our in-house big data language for the large-scale analysis and production of securities data - Research and development of market dynamics across multiple asset classes - Prototyping, testing, and validation of TradingHub’s proprietary models - supporting and coaching more junior team members Requirements - Proven financial markets experience, ideally within an investment bank or pricing-related firm - Proficiency with C#, Python or another object-oriented programming language - Evidence of exceptional mathematical and analytical skills - A clear understanding of market risk, preferably for fixed-income - Good knowledge of derivatives (e.g. options, swaps, futures etc.) - Good knowledge of database technologies such as SQL, Postgres etc. - Able to deliver projects to agreed deadlines with excellent prioritisation skills Benefits Life at TradingHub is a rewarding journey within a fast-growing company that thrives on innovation and collaboration. By combining the best of technology and global markets, we’re able to solve complex problems together and deliver meaningful results to our customers. Everybody has value to bring, and we welcome individuality as a key driving force behind our collective success. Rooted in everything that we do are our core values: Accountability, Ambition, Partnership and Trust. These values provide the foundation for a sustainable workplace culture that empowers you to grow, contribute, and become your best self. Employee Benefits: - Annual discretionary performance bonus (permanent employees only) - Hybrid working policy - Office lunches twice a week - Private medical insurance + dental cover - Extended parental leave (up to 6 months of fully paid maternity leave) - 25 days annual leave + bank holidays - Enhanced company pension plan - 5 days study leave towards professional qualifications - Salary sacrifice schemes - Death in service coverage Don’t tick every single requirement? Research shows that candidates from under-represented groups are less likely to apply unless they meet all the criteria. We are dedicated to building a diverse, equitable and inclusive workplace, so if this role excites you, please don't let our specification hold you back. Get in touch! TradingHub is an equal opportunities employer. We do not discriminate based on race, religion, ethnic or national origins, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, socio-economic background, responsibilities for dependants, physical or mental disability or other applicable legally protected characteristics. TradingHub selects candidates for interview based solely on their skills, experience and qualifications. We are committed to making our recruitment process accessible to all and we encourage candidates to inform us of any required adjustments. A full copy of our diversity, equity and inclusion policy will be made available to you upon request.", "summaryDescription" : "Senior Quantitative Developer at TradingHub. Skills: Quantitative development, Financial markets, Software productionisation. Develop financial pricing libraries. Develop calculators", "createdAt" : "2026-06-14T02:04:14.207", "lastUpdated" : "2026-06-15T08:38:53.289", "ingestTimestamp" : "2026-06-14T02:04:14.207", "mongoId" : "6a2c68ca74d8ee00a0904c4f", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "150k-200k", "hasSalary" : false, "allSkills" : [ "Mathematical analysis", "Financial modeling", "Risk assessment", "Database management", "Quantitative development", "Financial markets", "Software productionisation", "Pricing models", "Financial pricing", "Risk algorithms", "Securities data analysis", "Market dynamics research", "Model validation", "Prioritisation", "Market manipulation", "Asset classes", "Fixed-income risk", "Derivatives", "Options", "Swaps", "Futures" ], "skillCount" : 21, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Executive", "dataQualityScore" : 0.8888889, "_score" : 616.27856, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.98 }, { "id" : "69dde45c2beec4dd3d9a3f9e", "title" : "Postdoctoral Fellow - Computational and Quantitative Medicine", "company" : "City of Hope", "industry" : "Healthcare", "salary" : { "min" : 60000.0, "max" : 85000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Postdoctoral Fellow in the Biotech industry in Monrovia, California, adjusted for entry-level seniority." }, "location" : "United States-California-Monrovia", "locations" : [ "United States-California-Monrovia", "Post-doctoral Research", "Onsite, Days, Days" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T08:17:43.745", "fingerprint" : "5e58bc0dc6aa312fdbc404e13e9157060ab95138ff31668d6bed755cf363f48b", "source" : "taleo", "language" : "en", "applyUrl" : "https://aa067.taleo.net/careersection/ex/jobdetail.ftl?job=210304", "externalId" : "210304", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Monrovia", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "34.1483499,-118.0014517" } ], "locationText" : "Monrovia, California, United States", "minimumEducation" : "PhD", "technicalSkills" : "SQL, Python, R, Scala, Spark, Dbt, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Dbt Cloud, Delta Lake, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, SageMaker, Athena, GCP, Vertex AI, Azure, Synapse, ML Studio", "professionalSkills" : [ "Quantitative analysis", "Data engineering", "Machine learning", "Business intelligence", "Analytics engineering", "Data science" ], "hardSkillsList" : [ "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills" ], "hardSkills" : [ { "name" : "Statistical methods", "level" : "intermediate" }, { "name" : "ML frameworks", "level" : "intermediate" }, { "name" : "BI platforms", "level" : "intermediate" }, { "name" : "Cloud data stacks", "level" : "intermediate" }, { "name" : "Modelling skills", "level" : "intermediate" } ], "majorSkills" : "Data science, Data engineering, Machine learning, Business intelligence", "majorSkillsList" : [ "Data science", "Data engineering", "Machine learning", "Business intelligence" ], "toolProficiency" : [ "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy" ], "qualificationsBasic" : "PhD required, 5+ years experience, SQL proficiency required", "qualificationsPreferred" : "PhD preferred, Specific ML framework experience, Cloud platform certifications", "remoteFriendly" : false, "rawDescription" : "Join the forefront of groundbreaking research at the Beckman Research Institute of City of Hope, where we're changing lives and making a real difference in the fight against cancer, diabetes, and other life-threatening illnesses. Our dedicated and compassionate faculty and staff are driven by a common mission: Contribute to innovative approaches in predicting, preventing, and curing diseases, shaping the future of medicine through cutting-edge research. A Postdoctoral Research Fellow position is open under Dr. Nagarajan Vaidehi within the department of Computational and Quantitative Medicine. This project involves the development and application of interpretable machine learning methods to uncover allosteric regulation of disordered regions in the dynamics of G-protein coupled receptors to enable design of allosteric modulators. You will work on developing design principles of targeted protein degradation in collaboration with Pharma. For more information on Dr. Vaidehi’s lab please visit here . Your qualifications should include: · PhD or M.D. in Chemistry, Physics or Biochemistry with experience in protein dynamics studies. · Knowledgeable about concepts in statistical thermodynamics, in python scripting and C++ programming. · Familiarity with Molecular Dynamics methods and experience in code development is preferred. City of Hope employees pay is based on the following criteria: work experience, qualifications, and work location. City of Hope is an equal opportunity employer. To learn more about our Comprehensive Benefits, please CLICK HERE . United States-California-Monrovia", "summaryDescription" : "Postdoctoral Fellow - Computational and Quantitative Medicine at City of Hope. Skills: Data science, Data engineering, Machine learning, Business intelligence", "createdAt" : "2026-06-14T19:54:56.791", "lastUpdated" : "2026-06-16T08:17:43.745", "ingestTimestamp" : "2026-06-14T19:54:56.791", "mongoId" : "69dde45c2beec4dd3d9a3f9e", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 60000, "salaryAnnualMax" : 85000, "salaryBand" : "50k-75k", "hasSalary" : true, "allSkills" : [ "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills", "Data science", "Data engineering", "Machine learning", "Business intelligence", "Quantitative analysis", "Analytics engineering", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy" ], "skillCount" : 22, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.6666667, "_score" : 615.0699, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Biotech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6bb474d8ee00a09141c6", "title" : "Junior Quantitative Researcher", "company" : "Quantbox Research", "industry" : "FinTech", "salary" : { "min" : 1200000.0, "max" : 1800000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Junior Quantitative Researcher in Bengaluru, India, adjusted for FinTech industry and entry-level experience." }, "location" : "Bengaluru, Karnataka, India", "locations" : [ "Bengaluru", "Karnataka", "India", "Hong Kong", "Singapore", "Central", "Singapore" ], "timestamp" : "2026-06-15T09:44:34.706", "fingerprint" : "07f6bc3993293ef29611ff57c8f11d338065a4854797fc19967782c00fb2b4b9", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/quantboxresearchpte/jobs/4001979101", "externalId" : "4001979101", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Bengaluru", "state" : "Karnataka", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "12.9767936,77.5900820" } ], "locationText" : "Bengaluru, Karnataka, India", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 0, "experienceMaxYears" : 2, "experienceLevel" : "Entry", "technicalSkills" : "Python, C++, R", "softSkillsList" : [ "Independent thinking", "Creative approach" ], "softSkills" : [ { "name" : "Independent thinking" }, { "name" : "Creative approach" } ], "coreResponsibilities" : "Build models, Improve models", "teamCollaboration" : "Work alongside traders; Work alongside software developers; Work alongside engineering team", "qualificationsBasic" : "Bachelor's degree, 1-2 years of experience", "qualificationsPreferred" : "PhD in mathematics, PhD in computer science, PhD in statistics, PhD in physics, Research experience a plus, Trading experience a plus", "workSiteFlexibility" : "Onsite", "rawDescription" : "Quantbox is a technology-driven proprietary trading firm that specializes in systematic alpha research and electronic market-making on various exchanges. We trade across a multitude of asset classes and trading venues with significant market share. We are looking for Junior Quantitative Researcher/Trader to join our team. What you’ll need: You possess a bachelor's degree / PhD in mathematics, computer science, statistics, physics, or a related field 1-2 years of experience in research or trading a plus Ability to think independently and use creative approach in problem solving Familiarity with python, C++, R programming languages You will be responsible for building and improving the models that keeps us competitive in the market. You will work alongside the traders, software developers and our engineering scientist, you would learn, research, improve, test, build our trading algorithms to increase trading profitability. A typical day involves applying rigorous scientific method, machine learning techniques to a vast array of datasets in order to create insights on how the market behave. Quantbox is an equal opportunity employer. Quantbox is a place of friends and colleagues, where people convert their passion into action. We believe in togetherness that brings out the best in ourselves and our Company. Our open and casual work culture gives you the space to innovate and deliver. Everyone on the team is approachable. Employee remuneration packages are reviewed regularly to ensure that they remain competitive. In recognition of our employees’ contributions and performance, for full time permanent roles we provide: Competitive compensation 4 Weeks of paid vacation Medical insurance International team outing Quantbox is an equal opportunities employer.", "summaryDescription" : "Junior Quantitative Researcher at Quantbox Research. Build models. Improve models", "postedDate" : "2026-06-13T20:50:22.456", "createdAt" : "2026-06-13T20:50:22.456", "lastUpdated" : "2026-06-15T09:44:34.706", "ingestTimestamp" : "2026-06-13T20:50:22.456", "mongoId" : "6a2c6bb474d8ee00a09141c6", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Independent thinking", "Creative approach" ], "skillCount" : 2, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Junior", "dataQualityScore" : 1.0, "_score" : 606.7694, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c7c2b74d8ee00a094c829", "title" : "Quantitative Developer, Intern", "company" : "Man Group", "industry" : "FinTech", "salary" : { "min" : 120000.0, "max" : 240000.0, "currency" : "CNY", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an entry-level intern in FinTech in China, adjusted for company size and industry." }, "location" : "China", "locations" : [ "China" ], "timestamp" : "2026-06-15T12:02:15.073", "fingerprint" : "41ea312f02588658cfa5e916ad3690a0279d74417f650c3a8fce22fb04e8cf47", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/mangroup/jobs/4847708101", "externalId" : "4847708101", "industryFunction" : { }, "structuredLocations" : [ { "country" : "China", "continent" : "as", "workMode" : "onsite" } ], "locationText" : "China", "employmentType" : "INTERNSHIP", "rawDescription" : "About Man Group Man Group is a global alternative investment management firm focused on pursuing outperformance for sophisticated clients via our Systematic, Discretionary and Solutions offerings. Powered by talent and advanced technology, our single and multi-manager investment strategies are underpinned by deep research and span public and private markets, across all major asset classes, with a significant focus on alternatives. Man Group takes a partnership approach to working with clients, establishing deep connections and creating tailored solutions to meet their investment goals and those of the millions of retirees and savers they represent. Headquartered in London, we manage $227.6 billion* and operate across multiple offices globally. Man Group plc is listed on the London Stock Exchange under the ticker EMG.LN and is a constituent of the FTSE 250 Index. Further information can be found at www.man.com * As at 31 December 2025 Key Skills if you require help or information on reasonable adjustments as you apply for roles with us, please contact TalentAcquisition@man.com.", "summaryDescription" : "Quantitative Developer, Intern at Man Group", "postedDate" : "2026-06-14T03:08:01.891", "createdAt" : "2026-06-14T03:08:01.891", "lastUpdated" : "2026-06-15T12:02:15.073", "ingestTimestamp" : "2026-06-14T03:08:01.891", "mongoId" : "6a2c7c2b74d8ee00a094c829", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Entry", "dataQualityScore" : 0.7777778, "_score" : 606.7022, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c76fb74d8ee00a093b688", "title" : "Quantitative Trading Strategist", "company" : "Voleon", "industry" : "Trading", "salary" : { "min" : 160000.0, "max" : 200000.0, "currency" : "USD", "frequency" : "Yearly" }, "location" : "Berkeley, CA", "locations" : [ "Berkeley, CA" ], "timestamp" : "2026-06-15T05:22:08.550", "fingerprint" : "67404b9f8f52167ea15a903d78647dab59326618fdbcd4bf2cc5bd9a68bcc843", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/voleon/c295e1bc-e188-4da9-a9c3-fb7d430087e4/application", "externalId" : "c295e1bc-e188-4da9-a9c3-fb7d430087e4", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Berkeley", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "37.8708393,-122.2728630" } ], "locationText" : "Berkeley, California, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 3, "experienceMaxYears" : 5, "experienceLevel" : "Mid", "technicalSkills" : "Python, R", "professionalSkills" : [ "Algorithmic execution", "Securities lending", "Portfolio financing", "Market microstructure" ], "hardSkillsList" : [ "Statistical methods", "Production code development" ], "hardSkills" : [ { "name" : "Statistical methods", "level" : "intermediate" }, { "name" : "Production code development", "level" : "intermediate" } ], "majorSkills" : "Quantitative trading, AI/ML, Investment management", "majorSkillsList" : [ "Quantitative trading", "AI/ML", "Investment management" ], "coreResponsibilities" : "Measure algorithmic execution quality, Improve algorithmic execution quality, Conduct high quality research, Create relevant reports, Present findings, Write high-quality production code, Design new packages, Develop new packages, Design data pipelines, Develop data pipelines, Design production trading applications, Develop production trading applications, Collaborate with trading team, Collaborate with RnD team, Improve trading strategies, Provide domain expertise, Manage relationships external brokers, Manage relationships trading partners", "teamCollaboration" : "Across teams; Trading and RnD team members", "domainKnowledge" : "Market microstructure; Asset classes", "domainList" : [ "market-microstructure", "asset-classes" ], "domainSpecificKnowledge" : [ "Market microstructure", "Asset classes" ], "communicationSkills" : "Present research findings", "qualificationsBasic" : "3+ years quantitative trading experience, Bachelor's degree scientific quantitative discipline, Proficient in basic statistics, Comprehensive market microstructure understanding", "remoteFriendly" : false, "rawDescription" : "Voleon is a technology company that applies state-of-the-art AI and machine learning techniques to real-world problems in finance. For nearly two decades, we have led our industry and worked at the frontier of applying AI/ML to investment management. We have become a multibillion-dollar asset manager, and we have ambitious goals for the future. Your colleagues will include internationally recognized experts in artificial intelligence and machine learning research as well as highly experienced finance and technology professionals. In addition to our enriching and collegial working environment, we offer highly competitive compensation and benefits packages, technology talks by our experts, a beautiful modern office, daily catered lunches, and more. As a QTS, you will use deep markets knowledge alongside quantitative skills to improve the implementation of systematic trading strategies. Domains include improving algorithmic execution, securities lending, and portfolio financing across a variety of asset classes and markets. You will work at the intersection of trading and research on problems that require market domain expertise but also statistical and quantitative rigor. RESPONSIBILITIES - Measure and improve algorithmic execution quality across asset classes - Conduct high quality research across a variety of market related topics and asset classes. Create relevant reports and present findings across teams - Write high-quality production level code. Design and develop new packages, data pipelines and production trading applications - Collaborate with trading and RnD team members to improve our trading strategies - Provide domain expertise in market microstructure across asset classes to other members of trading and RnD - Manage relationships with external brokers and trading partners REQUIREMENTS - 3+ years of experience in a quantitative trading environment with an emphasis on quantitative research - Bachelor’s degree in a scientific or quantitative discipline - Highly capable in python, R, and SQL; with the ability to write production level code and develop across teams - Proficient in basic statistics with an ability to apply valid statistical methods to judge outcomes from real-world data - Comprehensive understanding of market micro-structure and a passion for markets - Ability to effectively communicate across teams and present research findings in a clear and concise manner “FRIENDS OF VOLEON” CANDIDATE REFERRAL PROGRAM If you have a great candidate in mind for this role and would like to have the potential to earn $7,500 if your referred candidate is successfully hired and employed by The Voleon Group, please use this form https://voleon.com/referrals/ to submit your referral. For more details regarding eligibility, terms and conditions please make sure to review the Voleon Referral Bonus Program https://voleon.com/assets/Voleon-Referral-Bonus-Program.pdf. EQUAL OPPORTUNITY EMPLOYER The Voleon Group is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.", "summaryDescription" : "Quantitative Trading Strategist at Voleon. Skills: Quantitative trading, AI/ML, Investment management. Measure algorithmic execution quality. Improve algorithmic execution quality", "createdAt" : "2026-06-13T22:06:41.300", "lastUpdated" : "2026-06-15T05:22:08.550", "ingestTimestamp" : "2026-06-13T22:06:41.300", "mongoId" : "6a2c76fb74d8ee00a093b688", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 160000, "salaryAnnualMax" : 200000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Statistical methods", "Production code development", "Quantitative trading", "AI/ML", "Investment management", "Algorithmic execution", "Securities lending", "Portfolio financing", "Market microstructure", "Asset classes" ], "skillCount" : 10, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Mid", "dataQualityScore" : 0.8888889, "_score" : 605.21704, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "69ce5e189bc74574cb674c1e", "title" : "Director (Regulation and Prequalification of Medicines and Health Products)", "industry" : "Healthcare", "salary" : { "min" : 220000.0, "max" : 320000.0, "currency" : "CHF", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Director level in Geneva, Switzerland within the Pharma industry, adjusted for seniority and full-time employment." }, "location" : "Switzerland-Geneva", "locations" : [ "Switzerland-Geneva", "Apr 8, 2026, 9:59:00 PM", "Switzerland-Geneva, " ], "timestamp" : "2026-06-16T01:05:19.308", "fingerprint" : "65d233d561d06ed67b153291f3de73cac6f422b79e9c9784474ab60ded786f99", "source" : "taleo", "language" : "en", "applyUrl" : "https://who.taleo.net/careersection/ex/jobdetail.ftl?job=382074", "externalId" : "382074", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Geneva", "country" : "Switzerland", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "46.2017559,6.1466014" } ], "locationText" : "Geneva, Switzerland", "employmentType" : "FULL_TIME", "experienceLevel" : "Director", "professionalSkills" : [ "Regulatory affairs", "Prequalification", "Risk management", "Legal analysis", "Compliance oversight" ], "hardSkillsList" : [ "Regulatory compliance", "Drug registration", "Health product approval" ], "hardSkills" : [ { "name" : "Regulatory compliance", "level" : "intermediate" }, { "name" : "Drug registration", "level" : "intermediate" }, { "name" : "Health product approval", "level" : "intermediate" } ], "majorSkills" : "Medicines regulation, Health products, Prequalification", "majorSkillsList" : [ "Medicines regulation", "Health products", "Prequalification" ], "coreResponsibilities" : "Oversee regulation of medicines, Manage prequalification of health products, Ensure compliance with regulatory requirements, Develop and implement regulatory strategies, Advise on legal and compliance matters, Conduct risk assessments, Monitor changes in regulations", "teamCollaboration" : "Collaborate with international health organizations; Work with regulatory bodies", "domainKnowledge" : "International regulatory frameworks", "domainList" : [ "international-regulatory-frameworks" ], "domainSpecificKnowledge" : [ "International regulatory frameworks" ], "communicationSkills" : "Regulatory reporting; Policy development", "documentationSkills" : "Regulatory submissions; Compliance documentation", "problemSolvingSkills" : "Regulatory problem solving; Compliance issue resolution", "specialRequirements" : "Fixed-term appointment", "qualificationsBasic" : "5+ years experience in regulatory affairs, Experience with medicines and health products, Experience in prequalification processes", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "D2 Fixed-term appointment 2", "summaryDescription" : "Director (Regulation and Prequalification of Medicines and Health Products). Skills: Medicines regulation, Health products, Prequalification. Oversee regulation of medicines. Manage prequalification of health products", "createdAt" : "2026-06-14T18:51:10.429", "lastUpdated" : "2026-06-16T01:05:19.308", "ingestTimestamp" : "2026-06-14T18:51:10.429", "mongoId" : "69ce5e189bc74574cb674c1e", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Regulatory compliance", "Drug registration", "Health product approval", "Medicines regulation", "Health products", "Prequalification", "Regulatory affairs", "Risk management", "Legal analysis", "Compliance oversight", "International regulatory frameworks" ], "skillCount" : 11, "jobCategory" : "operations", "jobSubcategory" : "legal", "seniorityLevel" : "Director", "dataQualityScore" : 0.7777778, "_score" : 603.6945, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Pharma", "llmIndustryConfidence" : 0.92 }, { "id" : "69cf3f072beec4dd3d93421e", "title" : "Quantitative UX Researcher", "company" : "Amazon Web Services, Inc.", "industry" : "Design, Cloud Computing", "salary" : { "min" : 130000.0, "max" : 176000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Seattle, Washington, USA", "locations" : [ "Seattle, Washington, USA" ], "timestamp" : "2026-06-15T04:25:29.969", "fingerprint" : "706e33469aeed1131c6161b0d169bd291f6fd5011c7161ad08e35ac25b2730c5", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/10381814/apply", "externalId" : "82c04ed8-855f-4683-87ae-79147868057f", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Seattle", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6038321,-122.3300620" } ], "locationText" : "Seattle, Washington, United States", "employmentType" : "FULL_TIME", "technicalSkills" : "Python, R, AI, ML", "professionalSkills" : [ "Behavioral analysis", "Causal inference", "Product direction", "Product decisions", "Product performance", "Customer needs", "Customer value", "AI-powered experiences" ], "hardSkillsList" : [ "Experimentation", "Analytics", "Quantitative research", "Mixed-methods research", "Study design", "Hypothesis definition", "Success metrics", "Data analysis", "Statistical analysis" ], "hardSkills" : [ { "name" : "Experimentation", "level" : "intermediate" }, { "name" : "Analytics", "level" : "intermediate" }, { "name" : "Quantitative research", "level" : "intermediate" }, { "name" : "Mixed-methods research", "level" : "intermediate" }, { "name" : "Study design", "level" : "intermediate" }, { "name" : "Hypothesis definition", "level" : "intermediate" }, { "name" : "Success metrics", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Statistical analysis", "level" : "intermediate" } ], "majorSkills" : "Quantitative UX Research, Applied AI, Experimentation, Causal inference", "majorSkillsList" : [ "Quantitative UX Research", "Applied AI", "Experimentation", "Causal inference" ], "coreResponsibilities" : "Lead quantitative research, Turn product questions into hypotheses, Define success metrics, Design studies, Generate actionable insights, Evaluate new ideas, Improve existing experiences, Make product decisions, Lead quantitative research for AI products, Own studies end to end, Frame research questions, Define hypotheses, Select research methods, Identify measures, Analyze results, Communicate recommendations, Design experiments, Run experiments, Design surveys, Run surveys, Conduct behavioral analyses, Define success metrics for AI experiences, Track success metrics, Combine findings across research, Combine findings with product usage, Combine findings with customer feedback, Generate clear insights, Generate practical product recommendations, Partner with product, Partner with design, Partner with engineering, Support build test learn approach, Inform decisions throughout product lifecycle", "teamCollaboration" : "Product teams; Design teams; Engineering teams", "domainKnowledge" : "AI-native applications; AI-powered experiences; AI innovation", "domainList" : [ "ai-native-applications", "ai-powered-experiences", "ai-innovation" ], "domainSpecificKnowledge" : [ "AI-native applications", "AI-powered experiences", "AI innovation" ], "problemSolvingSkills" : "Data-driven decision making", "qualificationsBasic" : "3+ years User Research, Master's degree in quantitative field, Experience with data analytics, Experience with AI/ML technologies, Knowledge of quantitative data analysis, Experience with Python or R", "qualificationsPreferred" : "Experience communicating research findings, Experience developing V1 products, Experience building scalable programs", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "We are seeking a Quantitative UX Researcher who is excited to help shape the future of AI-native business applications. This is an opportunity to influence product direction by helping teams understand how customers interact with AI-powered experiences and what drives adoption, trust, usability, and customer value. In this role, you will lead quantitative research that helps teams build, test, and learn faster. You will turn product questions into clear hypotheses, success metrics, well-designed studies, and actionable insights. Your work will help teams evaluate new ideas, improve existing experiences, and make better product decisions. This is a quant-first role with mixed-methods responsibilities as needed. We are looking for a researcher with strong skills in experimentation, analytics, behavioral analysis, and causal inference. You should be comfortable working in ambiguous, early-stage spaces and helping teams define how success should be measured for new AI-powered products. You will identify meaningful behavioral and attitudinal signals, measure product performance, and recommend improvements based on the evidence. Key job responsibilities - Lead quantitative and mixed-methods research for AI-powered products, including early-stage concepts and evolving customer experiences. - Own studies from end to end, including framing research questions, defining hypotheses, selecting methods, identifying measures, analyzing results, and communicating recommendations. - Design and run experiments, surveys, and behavioral analyses that help teams understand customer needs, product performance, and opportunities for improvement. - Define and track success metrics related to adoption, trust, usability, comprehension, and customer value in AI-powered experiences. - Combine findings across research, product usage, and customer feedback to generate clear insights and practical product recommendations. - Partner closely with product, design, and engineering to support a build, test, learn approach, where evidence informs decisions throughout the product lifecycle. About the team AWS Applied AI Solutions is an organization with ambitions to be a leading provider of business applications, leveraging Amazon's unique experience and expertise, used by millions of companies worldwide to manage day-to-day operations. Our mission is to accelerate our customers' businesses by delivering intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. The AWS Applied AI Solutions team is at the forefront of AI innovation, designing and building the next generation of intelligent business applications. We work closely with global Product, Engineering, Science, Marketing, and Business Development teams to deliver compelling AI-powered experiences that transform how businesses operate. Our research team plays a critical role in ensuring these AI solutions are not just technically advanced, but truly meet customer needs and drive meaningful customer outcomes. Basic Qualifications: - 3+ years of proven success leading User Research projects with demonstrated impact experience - Experience (end to end) with all aspects of research (study design, recruiting, moderation, analysis, reporting) - Have a portfolio demonstrating past work experience and deliverables (e.g., study plans, reports, personas) - Master's degree in a quantitative field - Experience working with data and leveraging analytics to make decisions - Experience with AI/ML technologies - Knowledge of quantitative data analysis and statistics - Experience with Python or R Preferred Qualifications: - Experience communicating research findings and analysis in both written and spoken channels - Experience developing and launching V1 products - Experience building scalable programs and repeatable scalable processes, levering various tools and methods to create scale and efficiency Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, NY, New York - 143,100.00 - 193,600.00 USD annually USA, WA, Seattle - 130,100.00 - 176,000.00 USD annually", "summaryDescription" : "Quantitative UX Researcher at Amazon Web Services, Inc.. Skills: Quantitative UX Research, Applied AI, Experimentation, Causal inference. Lead quantitative research. Turn product questions into hypotheses", "postedDate" : "2026-06-13T04:47:53.913", "createdAt" : "2026-06-13T04:47:53.913", "lastUpdated" : "2026-06-15T04:25:29.969", "ingestTimestamp" : "2026-06-13T04:47:53.913", "mongoId" : "69cf3f072beec4dd3d93421e", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/10381814/apply", "salaryAnnualMin" : 130000, "salaryAnnualMax" : 176000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Experimentation", "Analytics", "Quantitative research", "Mixed-methods research", "Study design", "Hypothesis definition", "Success metrics", "Data analysis", "Statistical analysis", "Quantitative UX Research", "Applied AI", "Causal inference", "Behavioral analysis", "Product direction", "Product decisions", "Product performance", "Customer needs", "Customer value", "AI-powered experiences", "AI-native applications", "AI innovation" ], "skillCount" : 21, "jobCategory" : "design", "dataQualityScore" : 0.8888889, "_score" : 595.52985, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology" }, { "id" : "6a2a660d74d8ee00a062bbc2", "title" : "Sr Risk Associate", "company" : "Amazon Pay (India) Private Limited", "industry" : "Corporate Operations, Risk Family, Retail", "salary" : { "min" : 2200000.0, "max" : 3500000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Risk Associate in FinTech in Bengaluru, India, adjusted for Amazon's company size and industry." }, "location" : "Bengaluru, Karnataka, IND", "locations" : [ "Bengaluru, Karnataka, IND" ], "certifications" : [ "ACAMS certification" ], "timestamp" : "2026-06-15T08:06:17.415", "fingerprint" : "97ec6c46c7b7b6ebbbf0e286d2126763bcf8cbb2c2e423dabeb18e04e2c039a3", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10442101/apply", "externalId" : "1cff2967-1154-43ce-897f-de05517c467d", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Bengaluru", "state" : "Karnataka", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "12.9767936,77.5900820" } ], "locationText" : "Bengaluru, Karnataka, India", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "professionalSkills" : [ "Risk management", "Compliance management" ], "hardSkillsList" : [ "Transaction monitoring", "Suspicious transaction reporting", "Regulatory reporting", "Customer risk categorization" ], "hardSkills" : [ { "name" : "Transaction monitoring", "level" : "intermediate" }, { "name" : "Suspicious transaction reporting", "level" : "intermediate" }, { "name" : "Regulatory reporting", "level" : "intermediate" }, { "name" : "Customer risk categorization", "level" : "intermediate" } ], "majorSkills" : "AML, Risk, Compliance", "majorSkillsList" : [ "AML", "Risk", "Compliance" ], "coreResponsibilities" : "Review of potential suspicious transactions, Conduct deep dives, Suspicious transaction reporting (STR) templatization, File suspicious transaction reports, Handle inquiries received from regulators, Allocate and track AML trainings, Manage customer risk categorization process, Track adherence to defined AML transaction monitoring process", "domainKnowledge" : "Anti-Money Laundering (AML); Payment systems", "domainList" : [ "anti-money-laundering-aml", "payment-systems" ], "domainSpecificKnowledge" : [ "Anti-Money Laundering (AML)", "Payment systems" ], "documentationSkills" : "Suspicious transaction reporting", "problemSolvingSkills" : "Deep dives", "qualificationsBasic" : "Bachelor's degree, Speak, write, and read fluently in English, Experience with Microsoft Office products and applications, Experience with Excel", "qualificationsPreferred" : "Experience in Anti-Money Laundering (AML), sanctions, fraud, or risk management, ACAMS certification", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "This role is for Sr Risk Analyst who will play a critical role in AML transaction monitoring process and will be responsible for review of escalated alerts and filing suspicious transaction reports with the reporting authorities. The incumbent will report directly to the Sr Risk Manager. The Job will entail the following: a. Review of potential suspicious transactions and conducting deep dives b. Suspicious transaction reporting (STR) templatization for onward filing to regulators c. handling of inquiries received from regulators d. allocation and tracking of AML trainings e. managing customer risk categorization process f. tracking adherence to defined AML transaction monitoring process Risk and Compliance continue to evolve and incumbent could be expected to work and manage new programs as per organizational priority. About the team Our vision is to make Amazon Pay as the most trusted, convenient and rewarding Payment Experience. Given the highly sensitive nature of Payments business, it is imperative to have robust Risk and Compliance function, to ensure adherence to regulatory compliance and risk management and that's where Risk and Compliance Solutions (RCS) fits in. Risk and Compliance Solutions (RCS) is responsible for operational and compliance risk management for all functions within Amazon Pay. The function is responsible for setting strong operational risk management framework, risk identification, assessment and continuous monitoring framework. In addition, the function also manages key regulatory compliance functions such as regulatory reporting, Anti money laundering program, External Audit engagements, and Governances. Basic Qualifications: - Bachelor's degree - Speak, write, and read fluently in English - Experience with Microsoft Office products and applications - Experience with Excel Preferred Qualifications: - Experience in Anti-Money Laundering (AML), sanctions, fraud, or risk management - ACAMS certification Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.", "summaryDescription" : "Sr Risk Associate at Amazon Pay (India) Private Limited. Skills: AML, Risk, Compliance. Review of potential suspicious transactions. Conduct deep dives", "postedDate" : "2026-06-13T19:26:01.562", "createdAt" : "2026-06-13T19:26:01.562", "lastUpdated" : "2026-06-15T08:06:17.415", "ingestTimestamp" : "2026-06-13T19:26:01.562", "mongoId" : "6a2a660d74d8ee00a062bbc2", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10442101/apply", "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Transaction monitoring", "Suspicious transaction reporting", "Regulatory reporting", "Customer risk categorization", "AML", "Risk", "Compliance", "Risk management", "Compliance management", "Anti-Money Laundering (AML)", "Payment systems", "ACAMS certification" ], "skillCount" : 12, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Senior", "dataQualityScore" : 1.0, "_score" : 575.50964, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c71ee74d8ee00a092f67d", "title" : "Associate Director, Quantitative Research", "company" : "M3USA", "industry" : "Market Research", "salary" : { "min" : 120000.0, "max" : 180000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Associate Director, Quantitative Research in London, UK, adjusted for Director seniority and the Healthcare industry." }, "location" : "London, England, United Kingdom", "locations" : [ "London", "England", "United Kingdom" ], "timestamp" : "2026-06-15T08:06:26.268", "fingerprint" : "be4712cb733bb0a7447e19a51b78cc1ab8c608e6862559fd2d838017688af481", "source" : "smartrecruiters", "language" : "en", "applyUrl" : "https://jobs.smartrecruiters.com/M3USA/744000131829575-associate-director-quantitative-research", "externalId" : "744000131829575", "industryFunction" : { }, "structuredLocations" : [ { "city" : "London", "state" : "England", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "51.5074456,-0.1277653" } ], "locationText" : "London, England, United Kingdom", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "mid", "professionalSkills" : [ "Project management", "Client service" ], "hardSkillsList" : [ "Workload distribution", "Profitability analysis" ], "hardSkills" : [ { "name" : "Workload distribution", "level" : "intermediate" }, { "name" : "Profitability analysis", "level" : "intermediate" } ], "majorSkills" : "Quantitative Research, Team management, Client relations", "majorSkillsList" : [ "Quantitative Research", "Team management", "Client relations" ], "coreResponsibilities" : "Manage team members, Mentor team members, Appraise team members, Develop team members, Monitor team KPIs, Distribute workload, Provide guidance to operations team, Manage project escalations, Partner with internal stakeholders, Address issues, Improve performance on research projects, Adapt processes, Develop processes, Initiate processes, Enhance systems, Investigate project escalations, Ensure project completion on time, Ensure client satisfaction, Monitor productivity, Monitor quality of data collection, Oversee billing process, Support best practices development, Support policies development, Execute client service improvement plans, Ensure collaboration with sales, Provide solution-oriented approach, Oversee training of new team members, Oversee training needs of current employees, Approve annual leave, Approve expense reports, Approve quarterly reviews", "teamCollaboration" : "Internal stakeholders; Sales team", "projectManagementSkills" : [ "Project management" ], "domainKnowledge" : "Healthcare research; Market research", "domainList" : [ "healthcare-research", "market-research" ], "domainSpecificKnowledge" : [ "Healthcare research", "Market research" ], "toolProficiency" : [ "Microsoft Office", "Excel", "Outlook", "Word" ], "communicationSkills" : "Written communication; Verbal communication", "problemSolvingSkills" : "Analytical skills; Problem-solving skills", "outcomesObjectives" : "Ensure projects complete on time; Ensure projects within budget; Ensure projects end with expected profitability", "qualificationsBasic" : "5+ years Market Research, 3+ years project management, 1+ year managing employees", "qualificationsPreferred" : "Experience in healthcare Market Research, Experience with complex market research projects", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "About M3: A Japanese global leader in the provision of ground-breaking and innovative technological and research solutions to the healthcare industry. The M3 Group operates in the US, Asia, and Europe with over 5.8 million physician members globally via its physician websites which include mdlinx.com, m3.com, research.m3.com, Doctors.net.uk, medigate.net, and medlive.cn. M3 Inc. is a publicly traded company on the Tokyo Stock Exchange (jp:2413, NIKKEI 225) with subsidiaries in major markets including the US, UK, Japan, South Korea, and China, and in 2020 was ranked in Forbes’ Global 2000 list. The M3 Group provides services to healthcare and the life science industry. In addition to market research, these services include medical education, ethical drug promotion, clinical development, job recruitment, and clinic appointment services. M3 has offices in Japan, UK, France, Germany, Brazil, Sweden, China, USA, and South Korea, as well as India. The mission of the Associate Director is to manage and oversee a Client service Team. The individual will be a leader for his/her team by directly coaching and mentoring the staff, building relationships with M3 clients, and working with the team on ensuring projects complete on time and within budget. The Associate Director will also assist with updating processes and internal systems to ensure the team is working efficiently and collaboratively. This is the ideal role for someone who has management experience in market research, specifically focused on online healthcare research. Essential Duties and Responsibilities: Including, but not limited to the following: * Manage, mentor, appraise and develop team members, monitoring team KPI’s and workload distribution. * Responsible for providing guidance and mentoring members of the operations team. * Responsible for managing project escalations to ensure the project is completed on time and within budget. This will require the candidate to partner with internal stakeholders to address issues and improve performance on research projects. * Working closely with senior management to adapt, develop and initiate processes, procedures, and system enhancements. * Investigating and managing project escalations. The Associate Director will be responsible for ensuring the project is completed on time and to the satisfaction of the client. * Monitoring productivity and quality of data collection of their team’s projects. * Overseeing the billing process of the team, and ensuring projects end with expected profitability. * Support the development and implementation of best practices and policies for client service * Execute client service improvement plans on allocated accounts, ensuring collaboration with sales and other members of the team, and providing a consistent and solution-oriented approach across each touch point of the client journey * Overseeing the training of any new team members, as well as the training needs of current employees. * Responsible for approving annual leave, expense reports, and quarterly reviews of their direct reports. ## Qualifications Education and Training Required: Bachelor’s degree or equivalent work experience preferred Minimum Experience: * 5+ years of experience in Market Research * 3+ years of project management experience * Experience in healthcare focused Market Research preferred * Minimum of 1 year of experience managing employees preferred * Experience with complex market research projects which could include programming, intricate sampling, international, translations, patients, or patient referrals (preferred) Knowledge, Skill, Ability: * Be a self-motivated individual with exceptional time management, organizational skills and attention to detail. * Able to work well meet deadlines and under pressure. * Have exceptional written and verbal communication skills. * Have strong Microsoft Office skills including Excel, Outlook, and Word. * Have well-developed analytical and problem-solving skills. * Have the ability to work autonomously and in a team environment to successfully meet departmental objectives. ## Additional Information * 25 days annual leave * Participation in an annual bonus scheme linked to the profitability of the business * Pension 4%/4% employee/employer contributions of qualifying earnings * Company’s medical cash plan. As part of the cash plan you have access to subsidised gym membership and a staff discount scheme * Cycle scheme #LI-LC1 #LI-Hybrid", "summaryDescription" : "Associate Director, Quantitative Research at M3USA. Skills: Quantitative Research, Team management, Client relations. Manage team members. Mentor team members", "postedDate" : "2026-06-12T07:41:30.000", "createdAt" : "2026-06-13T18:34:26.700", "lastUpdated" : "2026-06-15T08:06:26.268", "ingestTimestamp" : "2026-06-13T18:34:26.700", "mongoId" : "6a2c71ee74d8ee00a092f67d", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Workload distribution", "Profitability analysis", "Quantitative Research", "Team management", "Client relations", "Project management", "Client service", "Healthcare research", "Market research", "Microsoft Office", "Excel", "Outlook", "Word" ], "skillCount" : 13, "jobCategory" : "operations", "jobSubcategory" : "general", "seniorityLevel" : "Director", "dataQualityScore" : 1.0, "_score" : 575.1762, "daysOld" : 3, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Healthcare", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6fb074d8ee00a0925d66", "title" : "Associate Director, Quantitative Research", "company" : "M3USA", "industry" : "Market Research", "salary" : { "min" : 115000.0, "max" : 175000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Quantitative Research roles in London, adjusted for Director seniority and the Healthcare industry." }, "location" : "London, England, United Kingdom", "locations" : [ "London", "England", "United Kingdom" ], "timestamp" : "2026-06-15T05:39:37.397", "fingerprint" : "928a24c266af4996611a8f585d7919d1a6c12a8d764c76175520710f72d31440", "source" : "smartrecruiters", "language" : "en", "applyUrl" : "https://jobs.smartrecruiters.com/M3USA/744000131829575-associate-director-quantitative-research", "externalId" : "744000131829575", "industryFunction" : { }, "structuredLocations" : [ { "city" : "London", "state" : "England", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "51.5074456,-0.1277653" } ], "locationText" : "London, England, United Kingdom", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "mid", "professionalSkills" : [ "Market research", "Client service" ], "hardSkillsList" : [ "Workload distribution", "Data collection", "Profitability analysis" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Workload distribution", "level" : "intermediate" }, { "name" : "Data collection", "level" : "intermediate" }, { "name" : "Profitability analysis", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Quantitative Research, Client Management, Team Leadership", "majorSkillsList" : [ "Quantitative Research", "Client Management", "Team Leadership" ], "coreResponsibilities" : "Manage team members, Mentor team members, Appraise team members, Develop team members, Monitor team KPIs, Monitor workload distribution, Provide guidance to operations team, Manage project escalations, Ensure project completion on time, Ensure project completion within budget, Partner with internal stakeholders, Address project issues, Improve performance on research projects, Adapt processes, Develop processes, Initiate processes, Adapt procedures, Develop procedures, Initiate procedures, Adapt system enhancements, Develop system enhancements, Initiate system enhancements, Investigate project escalations, Ensure client satisfaction, Monitor productivity, Monitor quality of data collection, Oversee billing process, Support development of best practices, Support implementation of best practices, Support development of policies, Support implementation of policies, Execute client service improvement plans, Ensure collaboration with sales, Provide solution-oriented approach, Oversee training of new team members, Oversee training needs of current employees, Approve annual leave, Approve expense reports, Approve quarterly reviews", "teamCollaboration" : "Internal stakeholders; Sales team; Other team members", "projectManagementSkills" : [ "Project management" ], "domainKnowledge" : "Healthcare research; Online healthcare research", "domainList" : [ "healthcare-research", "online-healthcare-research" ], "domainSpecificKnowledge" : [ "Healthcare research", "Online healthcare research" ], "toolProficiency" : [ "Microsoft Office", "Excel", "Outlook", "Word" ], "communicationSkills" : "Written communication; Verbal communication", "problemSolvingSkills" : "Analytical skills; Problem-solving skills", "outcomesObjectives" : "Ensure projects complete on time; Ensure projects complete within budget; Ensure project completion to satisfaction; Ensure projects end with expected profitability", "qualificationsBasic" : "5+ years Market Research, 3+ years project management, 1+ year managing employees", "qualificationsPreferred" : "Experience in healthcare Market Research, Experience with complex market research projects", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "About M3: A Japanese global leader in the provision of ground-breaking and innovative technological and research solutions to the healthcare industry. The M3 Group operates in the US, Asia, and Europe with over 5.8 million physician members globally via its physician websites which include mdlinx.com, m3.com, research.m3.com, Doctors.net.uk, medigate.net, and medlive.cn. M3 Inc. is a publicly traded company on the Tokyo Stock Exchange (jp:2413, NIKKEI 225) with subsidiaries in major markets including the US, UK, Japan, South Korea, and China, and in 2020 was ranked in Forbes’ Global 2000 list. The M3 Group provides services to healthcare and the life science industry. In addition to market research, these services include medical education, ethical drug promotion, clinical development, job recruitment, and clinic appointment services. M3 has offices in Japan, UK, France, Germany, Brazil, Sweden, China, USA, and South Korea, as well as India. The mission of the Associate Director is to manage and oversee a Client service Team. The individual will be a leader for his/her team by directly coaching and mentoring the staff, building relationships with M3 clients, and working with the team on ensuring projects complete on time and within budget. The Associate Director will also assist with updating processes and internal systems to ensure the team is working efficiently and collaboratively. This is the ideal role for someone who has management experience in market research, specifically focused on online healthcare research. Essential Duties and Responsibilities: Including, but not limited to the following: * Manage, mentor, appraise and develop team members, monitoring team KPI’s and workload distribution. * Responsible for providing guidance and mentoring members of the operations team. * Responsible for managing project escalations to ensure the project is completed on time and within budget. This will require the candidate to partner with internal stakeholders to address issues and improve performance on research projects. * Working closely with senior management to adapt, develop and initiate processes, procedures, and system enhancements. * Investigating and managing project escalations. The Associate Director will be responsible for ensuring the project is completed on time and to the satisfaction of the client. * Monitoring productivity and quality of data collection of their team’s projects. * Overseeing the billing process of the team, and ensuring projects end with expected profitability. * Support the development and implementation of best practices and policies for client service * Execute client service improvement plans on allocated accounts, ensuring collaboration with sales and other members of the team, and providing a consistent and solution-oriented approach across each touch point of the client journey * Overseeing the training of any new team members, as well as the training needs of current employees. * Responsible for approving annual leave, expense reports, and quarterly reviews of their direct reports. ## Qualifications Education and Training Required: Bachelor’s degree or equivalent work experience preferred Minimum Experience: * 5+ years of experience in Market Research * 3+ years of project management experience * Experience in healthcare focused Market Research preferred * Minimum of 1 year of experience managing employees preferred * Experience with complex market research projects which could include programming, intricate sampling, international, translations, patients, or patient referrals (preferred) Knowledge, Skill, Ability: * Be a self-motivated individual with exceptional time management, organizational skills and attention to detail. * Able to work well meet deadlines and under pressure. * Have exceptional written and verbal communication skills. * Have strong Microsoft Office skills including Excel, Outlook, and Word. * Have well-developed analytical and problem-solving skills. * Have the ability to work autonomously and in a team environment to successfully meet departmental objectives. ## Additional Information * 25 days annual leave * Participation in an annual bonus scheme linked to the profitability of the business * Pension 4%/4% employee/employer contributions of qualifying earnings * Company’s medical cash plan. As part of the cash plan you have access to subsidised gym membership and a staff discount scheme * Cycle scheme #LI-LC1 #LI-Hybrid", "summaryDescription" : "Associate Director, Quantitative Research at M3USA. Skills: Quantitative Research, Client Management, Team Leadership. Manage team members. Mentor team members", "postedDate" : "2026-06-12T07:41:30.000", "createdAt" : "2026-06-13T16:58:21.464", "lastUpdated" : "2026-06-15T05:39:37.397", "ingestTimestamp" : "2026-06-13T16:58:21.464", "mongoId" : "6a2c6fb074d8ee00a0925d66", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Workload distribution", "Data collection", "Profitability analysis", "Leadership", "Mentoring", "Quantitative Research", "Client Management", "Team Leadership", "Market research", "Client service", "Project management", "Healthcare research", "Online healthcare research", "Microsoft Office", "Excel", "Outlook", "Word" ], "skillCount" : 17, "jobCategory" : "project-management", "jobSubcategory" : "Market Research (EU)", "dataQualityScore" : 1.0, "_score" : 575.1762, "daysOld" : 2, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Healthcare" }, { "id" : "6a305b76f292fd229cf5e059", "title" : "Associate Director, Information Security Risk", "company" : "EQT Group", "industry" : "FinTech", "salary" : { "min" : 360000.0, "max" : 540000.0, "currency" : "PLN", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market data for an Associate Director, Information Security Risk in Financial Services in Warsaw, Poland, adjusted for director-level seniority and full-time employment." }, "location" : "Warszawa, Masovian Voivodeship, Poland", "locations" : [ "Warszawa", "Masovian Voivodeship", "Poland" ], "certifications" : [ "CISM", "CRISC", "CISSP" ], "timestamp" : "2026-06-16T08:06:33.159", "fingerprint" : "952a1d4d8a31c3e333437b382c388dfa4b1e6fbad80af07de3bcbf4abb568f95", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/eqtpartners/jobs/4897613101", "externalId" : "4897613101", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Warszawa", "state" : "Masovian Voivodeship", "country" : "Poland", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "52.2333742,21.0711489" } ], "locationText" : "Warszawa, Masovian Voivodeship, Poland", "experienceMinYears" : 10, "experienceLevel" : "Director", "technicalSkills" : "DORA, NIS2, ISO 27001, NIST", "professionalSkills" : [ "Risk assessment", "Control design", "Governance design" ], "hardSkillsList" : [ "Information security risk", "Cybersecurity governance", "Technology risk", "Security controls", "Vendor risk assessments", "Incident response", "Cybersecurity technologies", "Cybersecurity architectures", "Cybersecurity solutions" ], "hardSkills" : [ { "name" : "Information security risk", "level" : "intermediate" }, { "name" : "Cybersecurity governance", "level" : "intermediate" }, { "name" : "Technology risk", "level" : "intermediate" }, { "name" : "Security controls", "level" : "intermediate" }, { "name" : "Vendor risk assessments", "level" : "intermediate" }, { "name" : "Incident response", "level" : "intermediate" }, { "name" : "Cybersecurity technologies", "level" : "intermediate" }, { "name" : "Cybersecurity architectures", "level" : "intermediate" }, { "name" : "Cybersecurity solutions", "level" : "intermediate" } ], "majorSkills" : "Information security risk, Cybersecurity governance, Regulatory frameworks", "majorSkillsList" : [ "Information security risk", "Cybersecurity governance", "Regulatory frameworks" ], "coreResponsibilities" : "Identify security risks, Assess security risks, Track security risks, Escalate material issues, Design security controls, Implement security controls, Draft information security policies, Maintain information security policies, Enforce information security policies, Lead implementation regulatory frameworks, Monitor emerging obligations, Oversee information security component, Define vendor security requirements, Track remediation identified gaps, Coordinate response activities, Ensure governance obligations met, Lead post-incident reviews, Produce board-ready reporting, Produce risk appetite dashboards, Produce briefing materials", "teamCollaboration" : "Across global footprint; Across functions; With CISO; With governance forums; With Technology teams", "domainKnowledge" : "Regulated financial services; Cross-border regulatory dynamics; Third-party vendor risk; Critical outsourcing; Cyber incident response; Information security policies; Security risk frameworks; Technology risk; Asset management; Private equity; Banking; Financial services", "domainList" : [ "regulated-financial-services", "cross-border-regulatory-dynamics", "third-party-vendor-risk", "critical-outsourcing", "cyber-incident-response", "information-security-policies", "security-risk-frameworks", "technology-risk", "asset-management", "private-equity", "banking", "financial-services" ], "domainSpecificKnowledge" : [ "Regulated financial services", "Cross-border regulatory dynamics", "Third-party vendor risk", "Critical outsourcing", "Cyber incident response", "Information security policies", "Security risk frameworks", "Technology risk", "Asset management", "Private equity", "Banking", "Financial services" ], "communicationSkills" : "Board-ready reporting; Risk appetite dashboards; Briefing materials; Senior audiences; Board-level audiences", "qualificationsBasic" : "10 years information security risk, 10 years cybersecurity governance, 10 years technology risk, Build security risk frameworks, Operate security risk frameworks, Implement regulatory frameworks, Lead third-party vendor risk assessments, Solid background incident response, Advise technology teams, Credibly challenge technology teams, Distil technical topics, Distil risk topics", "qualificationsPreferred" : "CISM, CRISC, CISSP, Experience international team, Experience matrix organisation, Familiarity digital tools, Familiarity workflow automation, Exposure data governance obligations, Contribute board reporting, Contribute senior governance reporting", "rawDescription" : "EQT is looking for an Associate Director, Information Security Risk to serve as the firm's subject matter expert on information security risk — translating complex cybersecurity and technology risk into clear governance frameworks and actionable business outcomes. This is a senior individual contributor role sitting within the CISO function, reporting directly to the CISO, and operating across a global, regulated financial services environment. About the Team Risk, Regulatory, Compliance identify, assess and track security risks across the firm and escalate material issues to the CISO and relevant governance forums. Design and implement pragmatic, proportionate security controls that balance risk reduction with business agility. Draft, maintain and enforce information security policies, standards and procedures aligned to regulatory requirements and industry best practice. Lead implementation of applicable regulatory frameworks across EQT's global footprint (including DORA, NIS2, ISO 27001 and NIST) and monitor the horizon for emerging obligations. Oversee the information security component of third-party vendor risk reviews, including critical outsourcing assessments; define vendor security requirements and track remediation of identified gaps. Play a central role in EQT's cyber incident response capability — coordinating response activities, ensuring governance obligations are met, and leading post-incident reviews. Produce high-quality, board-ready reporting, risk appetite dashboards and briefing materials for senior management and governance committees. About You You are a seasoned information security risk professional with a commercial mindset and a talent for making complex risk topics accessible to senior audiences. You build trust across functions naturally, hold your ground on risk positions constructively, and bring genuine intellectual rigour to governance and control design. What you'll bring (must-have): Around 10 years of experience in information security risk, cybersecurity governance, or technology risk within asset management, private equity, banking or financial services. Proven track record building and operating security risk and control frameworks in a regulated financial services environment. Hands-on experience implementing regulatory frameworks such as DORA, NIS2, ISO 27001 or NIST, with solid understanding of cross-border regulatory dynamics. Demonstrated experience leading third-party vendor risk assessments, including outsourcing and critical supplier reviews. Solid background in incident response, from operational coordination through to governance reporting and lessons learned. Deep working knowledge of cybersecurity technologies, architectures and solutions, sufficient to advise and credibly challenge Technology teams. Strong communication skills with the ability to distil complex technical and risk topics into concise, impactful materials for senior and board-level audiences. Nice to have: Relevant professional qualifications such as CISM, CRISC or CISSP. Experience working within an international team or matrix organisation. Familiarity with digital tools and workflow automation that enhance team efficiency and risk reporting. Exposure to data governance obligations and their intersection with information security risk. Prior experience contributing to board or senior governance committee reporting in a financial services context. What We Offer At EQT, you will join a global firm that operates at the intersection of technology, finance and impact. You will have direct access to senior leadership, meaningful scope to shape how information security risk is governed at a complex, internationally active firm, and the opportunity to work alongside colleagues who hold themselves and each other to a high standard. EQT supports continuous professional development and values diverse perspectives as a driver of better outcomes. Compensation We understand and believe that being a great place to work drives the best performance.At EQT, inclusion is a business imperative and it's embedded into our talent strategy, decision-making, and culture to ensure that every individual and team operates at their full potential. By doing so, we unlock better collaboration, stronger innovation, and superior investment outcomes. About EQT EQT is a purpose-driven global investment organization focused on active ownership strategies. With a Nordic heritage and a global mindset, EQT has a track record of over three decades of developing companies across multiple geographies, sectors and strategies. EQT has investment strategies covering all phases of a business’ development, from start-up to maturity. EQT has EUR ‌270 billion in total assets under management (EUR ‌‌141 billion in fee-generating assets under management), within two business segments – Private Capital and Real Assets. With its roots in the Wallenberg family’s entrepreneurial mindset and philosophy of long-term ownership, EQT is guided by a set of strong values and a distinct corporate culture. EQT manages and advises funds and vehicles that invest across the world with the mission to future-proof companies, generate attractive returns and make a positive impact with everything EQT does. EQT has offices in more than 25 countries across Europe, Asia and the Americas and has more than 1,900 employees. More info: www.eqtgroup.com Follow EQT on LinkedIn, X, YouTube and Instagram", "summaryDescription" : "Associate Director, Information Security Risk at EQT Group. Skills: Information security risk, Cybersecurity governance, Regulatory frameworks. Identify security risks. Assess security risks", "postedDate" : "2026-06-15T23:23:26.048", "createdAt" : "2026-06-15T23:23:26.048", "lastUpdated" : "2026-06-16T08:06:33.159", "ingestTimestamp" : "2026-06-15T23:23:26.048", "mongoId" : "6a305b76f292fd229cf5e059", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Information security risk", "Cybersecurity governance", "Technology risk", "Security controls", "Vendor risk assessments", "Incident response", "Cybersecurity technologies", "Cybersecurity architectures", "Cybersecurity solutions", "Regulatory frameworks", "Risk assessment", "Control design", "Governance design", "Regulated financial services", "Cross-border regulatory dynamics", "Third-party vendor risk", "Critical outsourcing", "Cyber incident response", "Information security policies", "Security risk frameworks", "Asset management", "Private equity", "Banking", "Financial services", "CISM", "CRISC", "CISSP" ], "skillCount" : 27, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Director", "dataQualityScore" : 0.8888889, "_score" : 572.65735, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Financial Services", "llmIndustryConfidence" : 0.98 }, { "id" : "6a30511af292fd229cefa89c", "title" : "VP of Financial Products & Marketplace", "industry" : "Finance", "salary" : { "min" : 120000.0, "max" : 180000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a VP of Financial Products & Marketplace in Bulgaria, adjusted for executive seniority and the FinTech industry." }, "location" : "US", "locations" : [ "US" ], "timestamp" : "2026-06-16T12:25:20.171", "fingerprint" : "56bc81dae031ccc9675ef48b6d27fd3d43a39ac6cc0bd94157e3b6ff1e83d4b6", "source" : "lever", "language" : "en", "applyUrl" : "https://jobs.lever.co/jobgether/03615ae2-d08c-439a-a6de-0a1a5d75f1bf/apply", "externalId" : "03615ae2-d08c-439a-a6de-0a1a5d75f1bf", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Bulgaria", "continent" : "eu", "workMode" : "remote" } ], "locationText" : "Bulgaria", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 8, "experienceMaxYears" : 12, "experienceLevel" : "Executive", "professionalSkills" : [ "Marketplace leadership", "Financial expertise", "Commercial expertise", "Marketplace economics", "Monetization models", "Unit economics optimization", "Strategic thinking", "Analytical thinking", "Cross-functional leadership", "Executive presence" ], "hardSkillsList" : [ "P&L management", "Revenue performance", "Financial outcomes", "Partnership development", "Vendor management", "Commercial negotiations", "Marketplace economics", "Monetization models", "Unit economics optimization", "Strategic planning", "Operational planning", "Cross-functional leadership", "Data analysis" ], "hardSkills" : [ { "name" : "P&L management", "level" : "intermediate" }, { "name" : "Revenue performance", "level" : "intermediate" }, { "name" : "Financial outcomes", "level" : "intermediate" }, { "name" : "Partnership development", "level" : "intermediate" }, { "name" : "Vendor management", "level" : "intermediate" }, { "name" : "Commercial negotiations", "level" : "intermediate" }, { "name" : "Marketplace economics", "level" : "intermediate" }, { "name" : "Monetization models", "level" : "intermediate" }, { "name" : "Unit economics optimization", "level" : "intermediate" }, { "name" : "Strategic planning", "level" : "intermediate" }, { "name" : "Operational planning", "level" : "intermediate" }, { "name" : "Cross-functional leadership", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" } ], "majorSkills" : "Marketplace leadership, Financial products, Partnership development, P&L management", "majorSkillsList" : [ "Marketplace leadership", "Financial products", "Partnership development", "P&L management" ], "coreResponsibilities" : "Set strategic direction, Ensure scalable execution, Define long-term vision, Define long-term strategy, Own marketplace performance, Build strategic partnerships, Negotiate strategic partnerships, Manage strategic partnerships, Design marketplace structure, Optimize marketplace structure, Drive cross-functional execution, Establish operational systems, Lead go-to-market strategies, Serve as executive sponsor, Influence company-wide prioritization, Influence company-wide investment decisions, Build high-performing team, Lead high-performing team", "teamCollaboration" : "Cross-functional execution; Product teams; Engineering teams; Sales teams; Operations teams; Ecosystem stakeholders", "domainKnowledge" : "Financial products marketplace; Marketplace economics; Monetization frameworks; Financial services; Fintech", "domainList" : [ "financial-products-marketplace", "marketplace-economics", "monetization-frameworks", "financial-services", "fintech" ], "domainSpecificKnowledge" : [ "Financial products marketplace", "Marketplace economics", "Monetization frameworks", "Financial services", "Fintech" ], "communicationSkills" : "Executive presentations; External partner presentations", "continuousLearning" : "Professional development; Executive growth opportunities", "problemSolvingSkills" : "Analytical thinking; Strategic thinking; Translate data into decisions", "outcomesObjectives" : "Ensure alignment with platform growth; Ensure alignment with monetization goals; Achieve revenue targets; Achieve margin targets; Achieve unit economics targets; Achieve long-term profitability targets; Ensure seamless marketplace delivery; Ensure marketplace scalability", "qualificationsBasic" : "8-12+ years of experience in marketplaces, Proven track record of owning P&L, Proven track record of owning revenue performance, Proven track record of owning marketplace financial outcomes, Experience in partnership development, Experience in vendor management, Experience in complex commercial negotiations, Ability to operate at strategic levels, Ability to operate at operational levels, Cross-functional leadership skills, Ability to influence senior stakeholders, Bachelor's degree", "qualificationsPreferred" : "Experience in financial services, Experience in fintech, Experience in adjacent digital product ecosystems, MBA or equivalent advanced experience", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "## Accountabilities This role is responsible for setting the strategic direction and commercial success of a financial products marketplace while ensuring scalable execution across partners, product, and operations. Define and lead the long-term vision and strategy for the financial products marketplace, ensuring alignment with overall platform growth and monetization goals Own marketplace performance including revenue, margin, unit economics, and long-term profitability targets Build, negotiate, and manage strategic partnerships with financial product providers, vendors, and ecosystem stakeholders Design and optimize marketplace structure including curation, assortment strategy, pricing models, and monetization frameworks Drive cross-functional execution with Product, Engineering, Sales, and Operations to ensure seamless marketplace delivery and scalability Establish scalable operational systems for onboarding, integration, reporting, and partner lifecycle management Lead go-to-market strategies for new financial products and marketplace offerings Serve as the executive sponsor for marketplace initiatives, influencing company-wide prioritization and investment decisions Build and lead a high-performing team responsible for marketplace growth, partnerships, and operations Requirements This role requires deep marketplace leadership experience combined with strong financial and commercial expertise, ideally within platform or fintech-driven environments. 8–12+ years of experience in marketplaces, platform businesses, fintech, or two-sided ecosystems, with significant leadership responsibility Proven track record of owning P&L, revenue performance, or marketplace financial outcomes at scale Strong experience in partnership development, vendor management, and complex commercial negotiations Deep understanding of marketplace economics, monetization models, and unit economics optimization Ability to operate at both strategic and operational levels, balancing vision with execution detail Strong cross-functional leadership skills with the ability to influence senior stakeholders without formal authority Experience working in financial services, fintech, or adjacent digital product ecosystems is highly preferred Strong analytical and strategic thinking skills with the ability to translate data into actionable business decisions Excellent communication skills and executive presence, with experience presenting to leadership teams and external partners Bachelor’s degree required; MBA or equivalent advanced experience preferred Benefits Competitive executive-level compensation with performance-based incentives Equity or long-term incentive opportunities tied to company growth Comprehensive health, dental, and vision insurance plans Flexible remote-first work environment within the United States Generous paid time off and holiday policies Retirement savings plan with employer contribution options Professional development and executive growth opportunities Opportunity to shape and scale a high-impact financial marketplace at the core of the business. ## Additional Information How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1", "summaryDescription" : "VP of Financial Products & Marketplace. Skills: Marketplace leadership, Financial products, Partnership development, P&L management. Set strategic direction. Ensure scalable execution", "postedDate" : "2026-06-15T15:11:56.444", "createdAt" : "2026-06-15T15:11:56.444", "lastUpdated" : "2026-06-16T12:25:20.171", "ingestTimestamp" : "2026-06-16T03:21:31.110", "mongoId" : "6a30511af292fd229cefa89c", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "P&L management", "Revenue performance", "Financial outcomes", "Partnership development", "Vendor management", "Commercial negotiations", "Marketplace economics", "Monetization models", "Unit economics optimization", "Strategic planning", "Operational planning", "Cross-functional leadership", "Data analysis", "Marketplace leadership", "Financial products", "Financial expertise", "Commercial expertise", "Strategic thinking", "Analytical thinking", "Executive presence", "Financial products marketplace", "Monetization frameworks", "Financial services", "Fintech" ], "skillCount" : 24, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "VP", "dataQualityScore" : 0.8888889, "_score" : 566.7989, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a305b76f292fd229cf5e05a", "title" : "Associate Director, Information Security Risk", "company" : "EQT Group", "industry" : "FinTech", "salary" : { "min" : 360000.0, "max" : 540000.0, "currency" : "PLN", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an Associate Director, Information Security Risk in Financial Services in Warsaw, Poland, adjusted for Director seniority and full-time employment." }, "location" : "Warszawa, Masovian Voivodeship, Poland", "locations" : [ "Warszawa", "Masovian Voivodeship", "Poland" ], "certifications" : [ "CISM", "CRISC", "CISSP" ], "timestamp" : "2026-06-16T08:55:33.446", "fingerprint" : "1002902146dbbaeebab6c88f26f44d9b30e387829be17cdefc2b9427c735de83", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/eqtpartners/jobs/4897327101", "externalId" : "4897327101", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Warszawa", "state" : "Masovian Voivodeship", "country" : "Poland", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "52.2333742,21.0711489" } ], "locationText" : "Warszawa, Masovian Voivodeship, Poland", "experienceMinYears" : 10, "experienceLevel" : "Director", "technicalSkills" : "DORA, NIS2, ISO 27001, NIST", "professionalSkills" : [ "Risk assessment", "Control design", "Governance design", "Incident response", "Vendor risk management", "Policy development", "Standards development", "Procedure development" ], "hardSkillsList" : [ "Information security risk", "Cybersecurity governance", "Technology risk", "Security controls", "Risk reporting", "Vendor security requirements", "Cyber incident response", "Board reporting", "Risk appetite dashboards" ], "softSkillsList" : [ "Intellectual rigour", "Constructive challenge" ], "hardSkills" : [ { "name" : "Information security risk", "level" : "intermediate" }, { "name" : "Cybersecurity governance", "level" : "intermediate" }, { "name" : "Technology risk", "level" : "intermediate" }, { "name" : "Security controls", "level" : "intermediate" }, { "name" : "Risk reporting", "level" : "intermediate" }, { "name" : "Vendor security requirements", "level" : "intermediate" }, { "name" : "Cyber incident response", "level" : "intermediate" }, { "name" : "Board reporting", "level" : "intermediate" }, { "name" : "Risk appetite dashboards", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Intellectual rigour" }, { "name" : "Constructive challenge" } ], "majorSkills" : "Information security risk, Cybersecurity governance, Technology risk, Regulatory frameworks", "majorSkillsList" : [ "Information security risk", "Cybersecurity governance", "Technology risk", "Regulatory frameworks" ], "coreResponsibilities" : "Translate cybersecurity risk, Translate technology risk, Design security controls, Implement security controls, Draft information security policies, Maintain information security policies, Enforce information security policies, Lead regulatory framework implementation, Monitor emerging obligations, Oversee vendor risk reviews, Define vendor security requirements, Track remediation of gaps, Coordinate incident response, Ensure governance obligations met, Lead post-incident reviews, Produce board-ready reporting, Produce risk appetite dashboards, Produce briefing materials", "teamCollaboration" : "Across global footprint; With CISO function; With governance forums; With Technology teams; With senior management; With governance committees", "domainKnowledge" : "Financial services environment; Cross-border regulatory dynamics; Cybersecurity technologies; Cybersecurity architectures; Cybersecurity solutions; Digital tools; Workflow automation; Data governance obligations", "domainList" : [ "financial-services-environment", "cross-border-regulatory-dynamics", "cybersecurity-technologies", "cybersecurity-architectures", "cybersecurity-solutions", "digital-tools", "workflow-automation", "data-governance-obligations" ], "domainSpecificKnowledge" : [ "Financial services environment", "Cross-border regulatory dynamics", "Cybersecurity technologies", "Cybersecurity architectures", "Cybersecurity solutions", "Digital tools", "Workflow automation", "Data governance obligations" ], "toolProficiency" : [ "Bloomberg Terminal", "Reuters Eikon", "FactSet" ], "communicationSkills" : "Board-level reporting; Senior audience communication", "continuousLearning" : "Continuous professional development", "problemSolvingSkills" : "Risk reduction; Risk mitigation", "qualificationsBasic" : "10 years information security risk, 10 years cybersecurity governance, 10 years technology risk, Build security risk frameworks, Operate security risk frameworks, Implement regulatory frameworks, Lead third-party vendor risk assessments, Solid background incident response, Advise technology teams, Credibly challenge technology teams, Distil technical topics, Distil risk topics", "qualificationsPreferred" : "CISM, CRISC, CISSP, Experience international team, Experience matrix organisation, Familiarity digital tools, Familiarity workflow automation, Exposure data governance obligations, Contribute board reporting, Contribute senior governance reporting", "rawDescription" : "EQT is looking for an Associate Director, Information Security Risk to serve as the firm's subject matter expert on information security risk — translating complex cybersecurity and technology risk into clear governance frameworks and actionable business outcomes. This is a senior individual contributor role sitting within the CISO function, reporting directly to the CISO, and operating across a global, regulated financial services environment. About the Team Risk, Regulatory, Compliance identify, assess and track security risks across the firm and escalate material issues to the CISO and relevant governance forums. Design and implement pragmatic, proportionate security controls that balance risk reduction with business agility. Draft, maintain and enforce information security policies, standards and procedures aligned to regulatory requirements and industry best practice. Lead implementation of applicable regulatory frameworks across EQT's global footprint (including DORA, NIS2, ISO 27001 and NIST) and monitor the horizon for emerging obligations. Oversee the information security component of third-party vendor risk reviews, including critical outsourcing assessments; define vendor security requirements and track remediation of identified gaps. Play a central role in EQT's cyber incident response capability — coordinating response activities, ensuring governance obligations are met, and leading post-incident reviews. Produce high-quality, board-ready reporting, risk appetite dashboards and briefing materials for senior management and governance committees. About You You are a seasoned information security risk professional with a commercial mindset and a talent for making complex risk topics accessible to senior audiences. You build trust across functions naturally, hold your ground on risk positions constructively, and bring genuine intellectual rigour to governance and control design. What you'll bring (must-have): Around 10 years of experience in information security risk, cybersecurity governance, or technology risk within asset management, private equity, banking or financial services. Proven track record building and operating security risk and control frameworks in a regulated financial services environment. Hands-on experience implementing regulatory frameworks such as DORA, NIS2, ISO 27001 or NIST, with solid understanding of cross-border regulatory dynamics. Demonstrated experience leading third-party vendor risk assessments, including outsourcing and critical supplier reviews. Solid background in incident response, from operational coordination through to governance reporting and lessons learned. Deep working knowledge of cybersecurity technologies, architectures and solutions, sufficient to advise and credibly challenge Technology teams. Strong communication skills with the ability to distil complex technical and risk topics into concise, impactful materials for senior and board-level audiences. Nice to have: Relevant professional qualifications such as CISM, CRISC or CISSP. Experience working within an international team or matrix organisation. Familiarity with digital tools and workflow automation that enhance team efficiency and risk reporting. Exposure to data governance obligations and their intersection with information security risk. Prior experience contributing to board or senior governance committee reporting in a financial services context. What We Offer At EQT, you will join a global firm that operates at the intersection of technology, finance and impact. You will have direct access to senior leadership, meaningful scope to shape how information security risk is governed at a complex, internationally active firm, and the opportunity to work alongside colleagues who hold themselves and each other to a high standard. EQT supports continuous professional development and values diverse perspectives as a driver of better outcomes. Compensation We understand and believe that being a great place to work drives the best performance.At EQT, inclusion is a business imperative and it's embedded into our talent strategy, decision-making, and culture to ensure that every individual and team operates at their full potential. By doing so, we unlock better collaboration, stronger innovation, and superior investment outcomes. About EQT EQT is a purpose-driven global investment organization focused on active ownership strategies. With a Nordic heritage and a global mindset, EQT has a track record of over three decades of developing companies across multiple geographies, sectors and strategies. EQT has investment strategies covering all phases of a business’ development, from start-up to maturity. EQT has EUR ‌270 billion in total assets under management (EUR ‌‌141 billion in fee-generating assets under management), within two business segments – Private Capital and Real Assets. With its roots in the Wallenberg family’s entrepreneurial mindset and philosophy of long-term ownership, EQT is guided by a set of strong values and a distinct corporate culture. EQT manages and advises funds and vehicles that invest across the world with the mission to future-proof companies, generate attractive returns and make a positive impact with everything EQT does. EQT has offices in more than 25 countries across Europe, Asia and the Americas and has more than 1,900 employees. More info: www.eqtgroup.com Follow EQT on LinkedIn, X, YouTube and Instagram", "summaryDescription" : "Associate Director, Information Security Risk at EQT Group. Skills: Information security risk, Cybersecurity governance, Technology risk, Regulatory frameworks. Translate cybersecurity risk. Translate technology risk", "postedDate" : "2026-06-15T23:24:48.348", "createdAt" : "2026-06-15T23:24:48.348", "lastUpdated" : "2026-06-16T08:55:33.446", "ingestTimestamp" : "2026-06-15T23:24:48.348", "mongoId" : "6a305b76f292fd229cf5e05a", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Information security risk", "Cybersecurity governance", "Technology risk", "Security controls", "Risk reporting", "Vendor security requirements", "Cyber incident response", "Board reporting", "Risk appetite dashboards", "Intellectual rigour", "Constructive challenge", "Regulatory frameworks", "Risk assessment", "Control design", "Governance design", "Incident response", "Vendor risk management", "Policy development", "Standards development", "Procedure development", "Financial services environment", "Cross-border regulatory dynamics", "Cybersecurity technologies", "Cybersecurity architectures", "Cybersecurity solutions", "Digital tools", "Workflow automation", "Data governance obligations", "CISM", "CRISC", "CISSP", "Bloomberg Terminal", "Reuters Eikon", "FactSet" ], "skillCount" : 34, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Director", "dataQualityScore" : 0.8888889, "_score" : 564.5779, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Financial Services", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2a45da74d8ee00a05d3cc5", "title" : "Quantitative Researcher for Risk and Research Engagement", "company" : "Comity", "industry" : "Business", "salary" : { "min" : 150000.0, "max" : 180000.0, "currency" : "USD", "frequency" : "Yearly" }, "location" : "Chicago", "locations" : [ "Chicago", "New York", "Bay Area" ], "timestamp" : "2026-06-13T18:42:26.753", "fingerprint" : "7a39c7705c0c2f14a03eb7955feb95dc3b270069da37c9302b6dc0fe3c83696a", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/comity/3bae151e-3645-4e2a-8555-cb37d7d8ea01/application", "externalId" : "3bae151e-3645-4e2a-8555-cb37d7d8ea01", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Chicago", "state" : "Illinois", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "41.8755616,-87.6244212" } ], "locationText" : "Chicago, Illinois, United States", "employmentType" : "FULL_TIME", "technicalSkills" : "Python, machine learning, optimization, statistics, probability, applied mathematics", "professionalSkills" : [ "Portfolio management", "Quantitative research", "Risk management", "Market dynamics", "Portfolio allocation", "Analytical infrastructure", "Market structure", "Portfolio behavior", "Risk drivers", "Trading platform", "Risk platform", "Alpha research", "Backtesting infrastructure", "Experimentation infrastructure", "Simulation infrastructure", "Quantitative models", "Risk analysis", "Scenario analysis", "Performance attribution", "Portfolio P&L", "Portfolio exposures", "Investment decision-making", "Risk decision-making", "Uncertainty analysis" ], "hardSkillsList" : [ "Statistical learning", "Convex optimization", "Quantitative modeling", "Risk analysis", "Scenario analysis", "Performance attribution", "Portfolio P&L analysis", "Exposure analysis", "Quantitative analysis" ], "softSkillsList" : [ "Intellectual rigor", "Operational rigor" ], "hardSkills" : [ { "name" : "Statistical learning", "level" : "intermediate" }, { "name" : "Convex optimization", "level" : "intermediate" }, { "name" : "Quantitative modeling", "level" : "intermediate" }, { "name" : "Risk analysis", "level" : "intermediate" }, { "name" : "Scenario analysis", "level" : "intermediate" }, { "name" : "Performance attribution", "level" : "intermediate" }, { "name" : "Portfolio P&L analysis", "level" : "intermediate" }, { "name" : "Exposure analysis", "level" : "intermediate" }, { "name" : "Quantitative analysis", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Intellectual rigor" }, { "name" : "Operational rigor" } ], "majorSkills" : "Quantitative research, Risk management, Portfolio analytics, Machine learning", "majorSkillsList" : [ "Quantitative research", "Risk management", "Portfolio analytics", "Machine learning" ], "coreResponsibilities" : "Analyze U.S. power markets, Identify market opportunities, Identify portfolio risks, Identify drivers of performance, Support portfolio construction, Support allocation decisions, Support alpha research, Improve backtesting infrastructure, Improve experimentation infrastructure, Improve simulation infrastructure, Drive research outcomes, Develop quantitative models, Track portfolio P&L, Analyze portfolio P&L, Track portfolio exposures, Analyze portfolio exposures, Deliver actionable insights, Support investment decision-making, Support risk decision-making, Combine quantitative analysis, Combine sound judgment, Scale trading platform, Scale risk platform", "teamCollaboration" : "Partner with Portfolio Managers; Partner with Risk Managers; Collaborate with engineering teams; Collaborate with research teams; Collaborate with leadership teams", "domainKnowledge" : "U.S. power markets; Wholesale electricity markets; Virtual trading; Congestion modeling; Nodal pricing; FTRs; Structured finance", "domainList" : [ "u-s-power-markets", "wholesale-electricity-markets", "virtual-trading", "congestion-modeling", "nodal-pricing", "ftrs", "structured-finance" ], "domainSpecificKnowledge" : [ "U.S. power markets", "Wholesale electricity markets", "Virtual trading", "Congestion modeling", "Nodal pricing", "FTRs", "Structured finance" ], "toolProficiency" : [ "Python" ], "communicationSkills" : "Communicate quantitative insights", "problemSolvingSkills" : "Dig into messy problems; Drive problems to resolution", "qualificationsBasic" : "quantitative foundations in statistics, quantitative foundations in optimization, quantitative foundations in probability, quantitative foundations in machine learning, quantitative foundations in applied mathematics, experience developing quantitative models, experience with performance attribution, experience with portfolio optimization, experience with systematic trading analytics, Python programmer, experience building analytical tooling, experience with large datasets, intuition for markets, intuition for portfolio behavior, intuition for risk, communicate quantitative insights clearly, intellectually rigorous, operationally dig into messy problems, drive problems to resolution", "qualificationsPreferred" : "Experience in U.S. wholesale electricity markets, Advanced degree in a quantitative discipline", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "\uD83C\uDFAF WHY WE EXIST We’re on a mission to improve the reliability, transparency, and efficiency of our energy systems, fostering a future with sustainable and abundant energy. To accomplish our aims, we’re leveraging state of the art statistical learning and convex optimization methods (AI) to build the financial rails of our future energy systems that will accelerate the deployment of clean energy resources. We envision energy systems that are efficient, autonomous, resilient, and powered by 100% renewable energy. \uD83E\uDDD7 WHO WE ARE Our founders (ex-Apple, Bluevine; ex-Affirm, Square, Google) are Stanford alumni with experience in complex systems, machine learning and structured finance. Our world-class investors, Maverick Ventures https://www.maverickventures.com/ and Caffeinated Capital https://caffeinatedcapital.com/, are aligned to our policy objectives and platform vision. We have hubs in New York City, Chicago, and San Francisco. THE ROLE This role sits at the intersection of portfolio management, quantitative research, and risk management. You will partner closely with Portfolio Managers, Risk Managers, and senior leadership to develop risk models, analyze power market dynamics, improve portfolio allocation decisions, and build the analytical infrastructure that supports our trading and risk platform. You will work directly with decision-makers across the organization to deepen our understanding of market structure, portfolio behavior, and risk drivers in U.S. power markets. This role is highly collaborative, analytical, and hands-on, with significant opportunity to shape our risk and portfolio analytics capabilities as the platform scales. In this role, you will: - Analyze U.S. power markets to identify market opportunities, portfolio risks, and drivers of performance - Partner directly with Portfolio Managers and Risk Managers to support portfolio construction, allocation decisions, and alpha research - Improve backtesting, experimentation, and simulation infrastructure to drive research outcomes - Develop quantitative models for risk analysis, scenario analysis, and performance attribution - Track and analyze portfolio P&L and exposures, delivering actionable insights to PMs and senior leadership - Support investment and risk decision-making under uncertainty by combining quantitative analysis and sound judgment - Collaborate closely with engineering, research, and leadership teams to scale Comity’s trading and risk platform WE’RE EXCITED ABOUT YOU BECAUSE: - You have strong quantitative foundations in statistics, optimization, probability, machine learning, or applied mathematics - You have experience developing quantitative models for portfolio analytics, risk management, or trading applications - You have experience with performance attribution, portfolio optimization, or systematic trading analytics - You are comfortable influencing Portfolio Managers, Risk Managers, and senior stakeholders in fast-moving environments - You are a strong Python programmer with experience building analytical tooling and working with large datasets - You have strong intuition for markets, portfolio behavior, and risk under changing market conditions - You communicate quantitative insights clearly to both technical and non-technical audiences - You are intellectually rigorous and operationally resilient; you dig into messy problems and drive them to resolution Nice to have - Experience in U.S. wholesale electricity markets, including virtual trading, congestion modeling, nodal pricing, or FTRs - Advanced degree in a quantitative discipline such as mathematics, statistics, computer science, engineering, physics, or economics LOCATION We have hubs in New York City, Chicago, and San Francisco. At Comity, we seek to recruit, develop, and retain the most talented people from a diverse candidate pool. Our priority is to ensure that all applicants are provided with fair and equal access to employment opportunities. Recruiting and hiring decisions are made without regard to race, color, religion, sex, national origin, age, disability, or any other class protected by law.", "summaryDescription" : "Quantitative Researcher for Risk and Research Engagement at Comity. Skills: Quantitative research, Risk management, Portfolio analytics, Machine learning. Analyze U.S. power markets. Identify market opportunities", "postedDate" : "2026-06-11T18:18:09.081", "createdAt" : "2026-06-11T18:18:09.081", "lastUpdated" : "2026-06-13T18:42:26.753", "ingestTimestamp" : "2026-06-11T18:18:09.081", "mongoId" : "6a2a45da74d8ee00a05d3cc5", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 150000, "salaryAnnualMax" : 180000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Statistical learning", "Convex optimization", "Quantitative modeling", "Risk analysis", "Scenario analysis", "Performance attribution", "Portfolio P&L analysis", "Exposure analysis", "Quantitative analysis", "Intellectual rigor", "Operational rigor", "Quantitative research", "Risk management", "Portfolio analytics", "Machine learning", "Portfolio management", "Market dynamics", "Portfolio allocation", "Analytical infrastructure", "Market structure", "Portfolio behavior", "Risk drivers", "Trading platform", "Risk platform", "Alpha research", "Backtesting infrastructure", "Experimentation infrastructure", "Simulation infrastructure", "Quantitative models", "Portfolio P&L", "Portfolio exposures", "Investment decision-making", "Risk decision-making", "Uncertainty analysis", "U.S. power markets", "Wholesale electricity markets", "Virtual trading", "Congestion modeling", "Nodal pricing", "FTRs", "Structured finance", "Python" ], "skillCount" : 42, "jobCategory" : "other", "jobSubcategory" : "business", "dataQualityScore" : 0.8888889, "_score" : 562.4348, "daysOld" : 2, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "energy systems" }, { "id" : "6a2c6b1a74d8ee00a0910403", "title" : "Quantitative Researcher - Deep Learning", "company" : "XTX Markets", "industry" : "FinTech", "salary" : { "min" : 150000.0, "max" : 250000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Quantitative Researcher in FinTech in London, UK, adjusted for company size and industry." }, "location" : "London, England, United Kingdom", "locations" : [ "London", "England", "United Kingdom" ], "timestamp" : "2026-06-15T13:20:22.233", "fingerprint" : "c609b569ead99a4f801b7c654f23ddec92e724cf64d212180fcb95f9e62381d7", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/xtxmarketstechnologies/jobs/7770152003", "externalId" : "7770152003", "industryFunction" : { }, "structuredLocations" : [ { "city" : "London", "state" : "England", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "51.5074456,-0.1277653" } ], "locationText" : "London, England, United Kingdom", "employmentType" : "FULL_TIME", "minimumEducation" : "PhD", "technicalSkills" : "Python, R, Scala, Spark, SQL, Deep learning, Machine learning, Statistics, Mathematics, Computer science, Physics", "professionalSkills" : [ "Research taste", "Mathematical depth", "Modelling practical", "Experimental taste", "Hypothesis formation", "Test design", "Ambiguous results reading", "Evidence interpretation", "Intellectual honesty" ], "hardSkillsList" : [ "Time-series prediction", "Cross-sectional prediction", "Representation improvement", "Objective improvement", "Optimization improvement", "Regularisation improvement", "Uncertainty estimation", "Evaluation methods", "Scaling improvement", "Robustness improvement", "Distribution shift handling", "Market feedback integration" ], "hardSkills" : [ { "name" : "Time-series prediction", "level" : "intermediate" }, { "name" : "Cross-sectional prediction", "level" : "intermediate" }, { "name" : "Representation improvement", "level" : "intermediate" }, { "name" : "Objective improvement", "level" : "intermediate" }, { "name" : "Optimization improvement", "level" : "intermediate" }, { "name" : "Regularisation improvement", "level" : "intermediate" }, { "name" : "Uncertainty estimation", "level" : "intermediate" }, { "name" : "Evaluation methods", "level" : "intermediate" }, { "name" : "Scaling improvement", "level" : "intermediate" }, { "name" : "Robustness improvement", "level" : "intermediate" }, { "name" : "Distribution shift handling", "level" : "intermediate" }, { "name" : "Market feedback integration", "level" : "intermediate" } ], "majorSkills" : "Deep learning, ML research, Forecasting systems, Modelling", "majorSkillsList" : [ "Deep learning", "ML research", "Forecasting systems", "Modelling" ], "coreResponsibilities" : "Do original research, Improve forecasting systems, Improve trading systems, Design deep learning models, Train deep learning models, Improve representations, Improve objectives, Improve optimisation, Improve regularisation, Improve uncertainty estimates, Improve evaluation methods, Improve scaling, Make models robust, Work with engineers, Work with technologists, Turn research into production, Learn market structure, Ask better modelling questions", "teamCollaboration" : "Flat team; Ideas challenged directly", "domainKnowledge" : "Financial instruments; Market structure; Trading systems; Time scales; Microseconds to weeks; Non-stationary data; Weak signals; Short-lived signals; Model evaluation; Costs; Latency; Risk; Capacity", "domainList" : [ "financial-instruments", "market-structure", "trading-systems", "time-scales", "microseconds-to-weeks", "non-stationary-data", "weak-signals", "short-lived-signals", "model-evaluation", "costs", "latency", "risk", "capacity" ], "domainSpecificKnowledge" : [ "Financial instruments", "Market structure", "Trading systems", "Time scales", "Microseconds to weeks", "Non-stationary data", "Weak signals", "Short-lived signals", "Model evaluation", "Costs", "Latency", "Risk", "Capacity" ], "problemSolvingSkills" : "Test hypotheses; Read ambiguous results; Change mind quickly", "qualificationsBasic" : "Deep practical understanding of modern deep learning, Mathematical and statistical foundations, Excellent programming ability, Comfort working close to implementation details, Good experimental taste, High standards, Intellectual honesty", "qualificationsPreferred" : "PhD or equivalent research experience, Experience training large models, Building ML systems at scale, Time-series modelling experience, Online learning experience, Continual learning experience, Reinforcement learning experience, Causal inference experience, Probabilistic modelling experience, Optimisation experience, Compilers experience, HPC experience, Low-latency systems experience, Experience taking research beyond prototype", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "The Firm XTX Markets is a leading algorithmic trading firm. We build models that forecast prices for more than 53,000 financial instruments across equities, fixed income, currencies, commodities and crypto. Those forecasts are used to trade on exchanges and other venues, and to provide liquidity to clients. The firm trades over $250bn a day across 35 countries, with over 300 people in London, Singapore, New York, Paris, Bristol, Mumbai, Yerevan and Kajaani. XTX is a technology business. Trading here is driven by research, large-scale computation and careful engineering. Over the last decade our models have moved from the econometric methods that gave the firm its name, through trees and neural networks, to modern deep learning. We expect that evolution to continue, and we are looking for researchers who can push it. The research platform is large by any standard, and particularly unusual in trading: well over 25,000 GPUs and more than 1 exabyte of usable storage, with further compute being built in Finland. The point is simple: good ideas should not be bottlenecked by data, infrastructure or compute. The Team This role sits in XTX's central Quantitative Research team, the group responsible for the firm's core forecasting research. The team reports directly to XTX's founder and is intentionally flat. There is little ceremony and little hierarchy; researchers are expected to have ideas, test them properly, argue from evidence and get useful work into the system. The work is modern ML research, not finance by another name. You do not need to have worked in trading. The best candidates usually have strong research taste, mathematical depth and the ability to make models work in practice. An interest in markets helps, because the domain is full of useful structure, but trading intuition can be built here. The Role Trading is a hard setting for machine learning in ways that are not always obvious from outside the industry. The data is enormous, messy, non-stationary and produced by other agents. Signals are weak and often short-lived. Evaluation is unforgiving: costs, latency, risk and capacity all matter, and a model that looks good in a backtest may still be useless in the market. The time scales also range from microseconds to weeks, so there is no single right abstraction. Your job will be to do original research that improves XTX's forecasting and trading systems. Depending on your background, that may mean: Designing and training deep learning models for large-scale time-series and cross-sectional prediction. Improving representations, objectives, optimisation, regularisation, uncertainty estimates, evaluation methods or scaling. Making models more robust under distribution shift and feedback from the market. Working with engineers and trading technologists to turn research into production systems. Learning enough market structure to ask better modelling questions. This is not about applying standard methods to tidy datasets. It is a place to do serious ML research on difficult data, with enough compute and infrastructure for ambitious ideas to be tested properly. What We Are Looking For Evidence of original technical ability in ML, statistics, mathematics, computer science, physics or another quantitative field. Publications are one route, but not the only one; strong industrial research or major open-source contributions can also be good evidence. Deep practical understanding of modern deep learning: architectures, objectives, optimisation, scaling, evaluation and failure modes. Strong mathematical and statistical foundations. Excellent programming ability and comfort working close to the details of implementation. Good experimental taste: forming hypotheses, designing clean tests, reading ambiguous results and changing your mind quickly when the evidence changes. High standards, intellectual honesty and the ability to work in a flat team where ideas are challenged directly. No finance background is needed; the important thing is being willing to learn the domain. Beneficial Experience PhD or equivalent research experience in a relevant technical field. Experience training large models or building ML systems at meaningful scale. Work in time-series modelling, online or continual learning, reinforcement learning, causal inference, probabilistic modelling, optimisation, compilers, HPC or low-latency systems. Experience taking research beyond a prototype. Benefits Key benefits include: Onsite gym, sauna and fitness classes. Extensive medical benefits, including onsite doctor and therapist. Breakfast and lunch provided daily. Support for caregivers, including emergency dependent care. King's Cross office. 25 days paid holiday per year, plus statutory holidays and paid sick days. Generous pension contributions.", "summaryDescription" : "Quantitative Researcher - Deep Learning at XTX Markets. Skills: Deep learning, ML research, Forecasting systems, Modelling. Do original research. Improve forecasting systems", "postedDate" : "2026-06-14T07:54:53.456", "createdAt" : "2026-06-14T07:54:53.456", "lastUpdated" : "2026-06-15T13:20:22.233", "ingestTimestamp" : "2026-06-14T07:54:53.456", "mongoId" : "6a2c6b1a74d8ee00a0910403", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "150k-200k", "hasSalary" : false, "allSkills" : [ "Time-series prediction", "Cross-sectional prediction", "Representation improvement", "Objective improvement", "Optimization improvement", "Regularisation improvement", "Uncertainty estimation", "Evaluation methods", "Scaling improvement", "Robustness improvement", "Distribution shift handling", "Market feedback integration", "Deep learning", "ML research", "Forecasting systems", "Modelling", "Research taste", "Mathematical depth", "Modelling practical", "Experimental taste", "Hypothesis formation", "Test design", "Ambiguous results reading", "Evidence interpretation", "Intellectual honesty", "Financial instruments", "Market structure", "Trading systems", "Time scales", "Microseconds to weeks", "Non-stationary data", "Weak signals", "Short-lived signals", "Model evaluation", "Costs", "Latency", "Risk", "Capacity" ], "skillCount" : 38, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "_score" : 559.6184, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c6fb074d8ee00a0925d60", "title" : "Senior Project Manager, Quantitative Research", "company" : "M3USA", "industry" : "Market Research", "salary" : { "min" : 85000.0, "max" : 125000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Project Manager in London, UK, adjusted for the healthcare industry and company size." }, "location" : "London, England, United Kingdom", "locations" : [ "London", "England", "United Kingdom" ], "timestamp" : "2026-06-15T05:29:54.088", "fingerprint" : "43002e93dd0562798a63b430adb22d6c6dad6314ed9f3f81a2d50d2b418ebbc4", "source" : "smartrecruiters", "language" : "en", "applyUrl" : "https://jobs.smartrecruiters.com/M3USA/744000131951899-senior-project-manager-quantitative-research", "externalId" : "744000131951899", "industryFunction" : { }, "structuredLocations" : [ { "city" : "London", "state" : "England", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "51.5074456,-0.1277653" } ], "locationText" : "London, England, United Kingdom", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 2, "experienceMaxYears" : 5, "experienceLevel" : "mid", "technicalSkills" : "Excel, Word", "professionalSkills" : [ "Market Research", "Data collection" ], "hardSkillsList" : [ "Project management" ], "hardSkills" : [ { "name" : "Project management", "level" : "intermediate" } ], "majorSkills" : "Project lifecycle management, Client communication, Budget management", "majorSkillsList" : [ "Project lifecycle management", "Client communication", "Budget management" ], "coreResponsibilities" : "Manage all aspects of the project lifecycle, Manage project budgets, Communicate to the client on progress, Troubleshoot and provide solutions, Ensure completion to deadline, Ensure Profiles, Health standards are met, Coordinate day-to-day activities, Resolve issues, Record issues, Report issues, Review all project documentation, Identify issues that jeopardise project completion, Provide recommendations to client service, Obtain revised quote on project, Manage internal project kick off meeting, Review materials, Finalize all project requirements, Determine timelines and schedules, Work directly with the client, Review all project materials, Make changes as needed, Provide consistent updates to client, Provide recommendations to panel team, Maximize sample, in field, Ensure the project is completed on time, Ensure all panelists receive incentive payments, Provide Finance team with financial metrics, Complete billing, Invoice deliver final bill to client", "teamCollaboration" : "Client services; Sales team; Panel team; Programming team; Finance team", "projectManagementSkills" : [ "Project lifecycle management", "Budget management", "Timeline management", "Schedule management" ], "domainKnowledge" : "Healthcare data collection; Market research", "domainList" : [ "healthcare-data-collection", "market-research" ], "domainSpecificKnowledge" : [ "Healthcare data collection", "Market research" ], "toolProficiency" : [ "Decipher", "Microsoft Office", "Excel", "Word" ], "communicationSkills" : "Client communication", "documentationSkills" : "Project documentation", "problemSolvingSkills" : "Troubleshooting; Problem resolution", "outcomesObjectives" : "Complete projects in a timely manner; Complete projects in a cost effective manner", "qualificationsBasic" : "3+ years experience in Marketing Research, Demonstrated proficiency with Decipher or similar platform, Microsoft Office, advanced proficiency in Excel, advanced proficiency in Word, Proven ability to manage multiple projects, meet aggressive deadlines, high level of detail", "qualificationsPreferred" : "Experience in Healthcare data collections", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "About M3: A Japanese global leader in the provision of ground-breaking and innovative technological and research solutions to the healthcare industry. The M3 Group operates in the US, Asia, and Europe with over 5.8 million physician members globally via its physician websites which include mdlinx.com, m3.com, research.m3.com, Doctors.net.uk, medigate.net, and medlive.cn. M3 Inc. is a publicly traded company on the Tokyo Stock Exchange (jp:2413, NIKKEI 225) with subsidiaries in major markets including the US, UK, Japan, South Korea, and China, and in 2020 was ranked in Forbes’ Global 2000 list. The M3 Group provides services to healthcare and the life science industry. In addition to market research, these services include medical education, ethical drug promotion, clinical development, job recruitment, and clinic appointment services. M3 has offices in Japan, UK, France, Germany, Brazil, Sweden, China, USA, and South Korea, as well as India.. The Senior Project Manager primary responsibility is to manage all aspects of the project lifecycle for data collection from initiation to completion which includes managing project budgets, communicating to the client on progress in field, trouble shooting and providing solutions to aid completion to deadline and ensuring that Profiles, Health standards are met on all aspects of the process and coordinating the day-to-day activities involved with running individual projects and resolving, recording and reporting issues that may jeopardize the team’s ability to complete the projects in a timely and cost effective manner. * Review all project documentation provided by client services with manager and identify issues that jeopardise the ability to complete the project on time and within budget or impact the project’s gross margin. If necessary, provide recommendations to client service and partner with them to obtain revised quote on project. * Manage internal project kick off meeting with sales, panel and programming to review materials, finalize all project requirements and determine timelines and schedules. Work directly with the client to review all project materials and schedule and make changes as needed. * Provide consistent updates to client on status on project during fielding process on a frequent basis either via email or phone. Provide recommendations to panel team to maximize sample while in field. * Ensure the project is completed on time and ensure all panelists receive incentive payments in a timely manner. Provide Finance team will all financial metrics required to complete billing and invoice process; deliver final bill to client. ## Qualifications * BA/BS degree in Market Research, Psychology or Sociology, Economics, Business Administration or related field * 3+ years experience in Marketing Research preferred * Experience in Healthcare data collections preferred * Demonstrated proficiency with Decipher or similar platform, Microsoft Office, advanced proficiency in Excel and Word * Proven ability to manage multiple projects and meet aggressive deadlines with a high level of detail ## Additional Information * 25 days annual leave * Participation in an annual bonus scheme linked to the profitability of the business * Pension 4%/4% employee/employer contributions of qualifying earnings * Company’s medical cash plan. As part of the cash plan you have access to subsidised gym membership and a staff discount scheme * Cycle scheme #LI-LC1 #LI-Hybrid", "summaryDescription" : "Senior Project Manager, Quantitative Research at M3USA. Skills: Project lifecycle management, Client communication, Budget management. Manage all aspects of the project lifecycle. Manage project budgets", "postedDate" : "2026-06-12T17:41:32.000", "createdAt" : "2026-06-13T13:28:29.651", "lastUpdated" : "2026-06-15T05:29:54.088", "ingestTimestamp" : "2026-06-13T13:28:29.651", "mongoId" : "6a2c6fb074d8ee00a0925d60", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "75k-100k", "hasSalary" : false, "allSkills" : [ "Project management", "Project lifecycle management", "Client communication", "Budget management", "Market Research", "Data collection", "Timeline management", "Schedule management", "Healthcare data collection", "Market research", "Decipher", "Microsoft Office", "Excel", "Word" ], "skillCount" : 14, "jobCategory" : "research", "jobSubcategory" : "Market Research (EU)", "dataQualityScore" : 1.0, "_score" : 557.29346, "daysOld" : 2, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Healthcare" }, { "id" : "6a2ab6cf74d8ee00a06e1b2a", "title" : "Senior Quantitative Treasury & ALM Risk Analyst", "company" : "Ebury", "industry" : "FinTech", "salary" : { "min" : 60000.0, "max" : 85000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Quantitative Treasury & ALM Risk Analyst in Madrid, Spain, adjusted for the FinTech industry and company size." }, "location" : "Madrid", "locations" : [ "Madrid" ], "timestamp" : "2026-06-14T22:42:20.360", "fingerprint" : "c97c9d22af7206a1e72d2961f469c6b09be7ddb85e4cd052128648ad6f8404d1", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://ebury.com/company/careers/job?gh_jid=4894997101", "externalId" : "4894997101", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Madrid", "country" : "Spain", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "40.4167820,-3.7035070" } ], "locationText" : "Madrid, Spain", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, SQL, NumPy, Pandas", "professionalSkills" : [ "Quantitative analysis", "Risk modelling", "Hedging strategies", "Interest rate risk", "IFRS valuation", "Delta attribution", "Pricing strategies", "Revenue optimization" ], "hardSkillsList" : [ "Liquidity risk simulations", "VaR99 calculations", "Portfolio correlation analysis", "DV01 analysis", "Code refactoring", "Code optimization" ], "softSkillsList" : [ "Creative thinking", "Innovative thinking", "Analytical skills", "Problem-solving skills", "Curiosity", "Drive to learn" ], "hardSkills" : [ { "name" : "Liquidity risk simulations", "level" : "intermediate" }, { "name" : "VaR99 calculations", "level" : "intermediate" }, { "name" : "Portfolio correlation analysis", "level" : "intermediate" }, { "name" : "DV01 analysis", "level" : "intermediate" }, { "name" : "Code refactoring", "level" : "intermediate" }, { "name" : "Code optimization", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Creative thinking" }, { "name" : "Innovative thinking" }, { "name" : "Analytical skills" }, { "name" : "Problem-solving skills" }, { "name" : "Curiosity" }, { "name" : "Drive to learn" } ], "majorSkills" : "Quantitative Treasury, ALM Risk Modelling, Quantitative finance", "majorSkillsList" : [ "Quantitative Treasury", "ALM Risk Modelling", "Quantitative finance" ], "coreResponsibilities" : "Assist in development and implementation of quantitative risk, Contribute to simulation of balance sheet evolution, Develop multi-entity, multi-currency hedging strategies, Support mapping of interest rate risk, Automate hedging strategies, Participate in IFRS valuation projects, Participate in delta attribution projects, Link market impacts to revenue drivers, Contribute to refactoring and optimization of code, Assist in analysis of pricing strategies, Assist in analysis of revenue optimization strategies, Document quantitative findings, Present quantitative findings to team, Brainstorm ideas to innovate current processes", "teamCollaboration" : "Collaborative team environment", "domainKnowledge" : "Liquidity risk; Interest rate risk; IFRS valuation; Quantitative finance; Risk modeling", "domainList" : [ "liquidity-risk", "interest-rate-risk", "ifrs-valuation", "quantitative-finance", "risk-modeling" ], "domainSpecificKnowledge" : [ "Liquidity risk", "Interest rate risk", "IFRS valuation", "Quantitative finance", "Risk modeling" ], "toolProficiency" : [ "Python", "SQL" ], "communicationSkills" : "Communication skills; Presentation skills; Explain complex concepts", "documentationSkills" : "Documentation skills", "problemSolvingSkills" : "Problem-solving skills", "qualificationsBasic" : "+5 years of experience in quantitative analysis or programming", "qualificationsPreferred" : "Experience in quantitative finance or data analysis", "workSiteFlexibility" : "Onsite", "rawDescription" : "Ebury helps ambitious businesses unlock global growth, and we take the same approach with our people. We encourage innovation and movement, collaboration and problem-solving, and foster an environment where everyone can feel they belong, are valued, supported and empowered to succeed. If you’re a collaborator who wants to help transform how businesses operate globally, get in touch - we’d love to discuss how Ebury can accelerate your career so you can shape the future. Quantitative Treasury/ALM Risk Modelling we redefine them. What you’ll do Assist in the development and implementation of advanced quantitative risk models, including liquidity risk simulations, VaR99 calculations, and portfolio correlation analysis. Contribute to the simulation of balance sheet evolution and the development of multi-entity, multi-currency hedging strategies. Support the mapping of interest rate risk through DV01 analysis and the automation of hedging strategies. Participate in IFRS valuation and delta attribution projects, linking market impacts to revenue drivers. Contribute to the refactoring and optimization of our code using Python and SQL. Assist in the analysis of pricing and revenue optimization strategies. Document and present quantitative findings to the team. Brainstorm and contribute ideas to innovate current processes. What you’ll need +5 years of experience in quantitative analysis or programming. Proficiency in Python (NumPy, Pandas) and SQL. Experience in quantitative finance or data analysis would be a plus. A strong passion for quantitative financial mathematics and quantitative analysis. Creative and innovative thinking, with a desire to challenge existing methodologies. Analytical and problem-solving skills. Communication, documentation and presentation skills with the ability to explain complex concepts clearly and concisely. Curiosity and a drive to learn complex financial concepts. Ability to work effectively in a collaborative team environment. Confident communication in English, both written and spoken. Open to candidates from diverse academic backgrounds, provided they demonstrate a strong interest and aptitude for quantitative finance and risk modeling. Why Ebury? Competitive Starting Salary with an annual discretionary bonus that truly rewards your performance from day one. Dedicated Mentorship: Learn directly from experienced managers who are invested in your success. Cutting-Edge Technology: Leverage state-of-the-art tailor made tools and systems that enable you to perform at your best. Clear, Accelerated Career Progression: Defined pathways to leadership and specialist roles within Ebury. Dynamic & Supportive Culture: Work in a collaborative environment where teamwork and personal growth are prioritized. Generous Benefits Package: Access competitive benefits tailored to your location, which typically include health care and social benefits. Central Leon Office: A fantastic location with excellent transport links. Ready to launch your career with a global FinTech? Click the ‘Apply’ Today and discover your potential at Ebury! #LI-GC2 #LI-HYBRID About us Ebury delivers sophisticated, integrated solutions — business accounts, hedging, and financing — on a single platform with a seamless workflow. Our success is built on a simple premise and singular purpose: To help businesses operate and scale globally. Since its founding in 2009, Ebury has always been a fast-growing leader in fintech. Today, we bring together 1,800+ Eburians across nearly 70 cities and we’re always looking to add to our team. At the heart of our offering is a proprietary platform, purpose-built to help businesses seamlessly streamline and manage global cash flow. We focus on continuous product evolution and innovation to build the infrastructure for borderless growth and help our clients scale at every stage. The opportunities at Ebury are as diverse as our people, ranging from business development to engineering roles across our tech pillars. We believe in inclusion. We stand against discrimination in all forms and are against the intolerance of differences that makes us a modern and successful organisation. At Ebury, you can be whoever you want to be and still feel a sense of belonging no matter your story.", "summaryDescription" : "Senior Quantitative Treasury & ALM Risk Analyst at Ebury. Skills: Quantitative Treasury, ALM Risk Modelling, Quantitative finance. Assist in development and implementation of quantitative risk. Contribute to simulation of balance sheet evolution", "postedDate" : "2026-06-12T00:55:49.515", "createdAt" : "2026-06-12T00:55:49.515", "lastUpdated" : "2026-06-14T22:42:20.360", "ingestTimestamp" : "2026-06-12T00:55:49.515", "mongoId" : "6a2ab6cf74d8ee00a06e1b2a", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "50k-75k", "hasSalary" : false, "allSkills" : [ "Liquidity risk simulations", "VaR99 calculations", "Portfolio correlation analysis", "DV01 analysis", "Code refactoring", "Code optimization", "Creative thinking", "Innovative thinking", "Analytical skills", "Problem-solving skills", "Curiosity", "Drive to learn", "Quantitative Treasury", "ALM Risk Modelling", "Quantitative finance", "Quantitative analysis", "Risk modelling", "Hedging strategies", "Interest rate risk", "IFRS valuation", "Delta attribution", "Pricing strategies", "Revenue optimization", "Liquidity risk", "Risk modeling", "Python", "SQL" ], "skillCount" : 27, "jobCategory" : "other", "jobSubcategory" : "treasury", "dataQualityScore" : 0.8888889, "_score" : 552.00287, "daysOld" : 2, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech" }, { "id" : "6a2c7c2b74d8ee00a094c83a", "title" : "Senior Quantitative Researcher - Macro", "company" : "Man Group", "industry" : "Banking", "salary" : { "min" : 150000.0, "max" : 250000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Quantitative Researcher in London, UK, adjusted for the financial services industry and a large company size." }, "location" : "London", "locations" : [ "London" ], "timestamp" : "2026-06-15T03:20:54.912", "fingerprint" : "ba85dc9218df5216bb9256c3e9d931b95402fb9d10c51323ac42edb4bdbdbbde", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/mangroup/jobs/4724414101", "externalId" : "4724414101", "industryFunction" : { }, "structuredLocations" : [ { "city" : "London", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "51.5074456,-0.1277653" } ], "locationText" : "London, United Kingdom", "experienceMinYears" : 4, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, SQL", "professionalSkills" : [ "Alpha signal research", "Live trading", "Predictor design", "Portfolio construction", "Risk analysis", "Transaction cost analysis", "Data handling" ], "hardSkillsList" : [ "Quantitative research", "Systematic trading", "Futures trading", "FX trading", "Data analysis" ], "softSkillsList" : [ "Intellectual honesty", "Mentoring", "Analytic approach", "Self-organised", "Interpersonal", "Confident communicator" ], "hardSkills" : [ { "name" : "Quantitative research", "level" : "intermediate" }, { "name" : "Systematic trading", "level" : "intermediate" }, { "name" : "Futures trading", "level" : "intermediate" }, { "name" : "FX trading", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Intellectual honesty" }, { "name" : "Mentoring" }, { "name" : "Analytic approach" }, { "name" : "Self-organised" }, { "name" : "Interpersonal" }, { "name" : "Confident communicator" } ], "majorSkills" : "Quantitative research, Systematic trading, Futures, FX", "majorSkillsList" : [ "Quantitative research", "Systematic trading", "Futures", "FX" ], "coreResponsibilities" : "Research alpha signals, Live trade alpha signals, Design predictors, Analyze predictors, Construct portfolios, Analyze risk, Mitigate transaction costs, Handle large data sets", "teamCollaboration" : "Quantitative researchers; Technologists; Traders; Senior stakeholders", "domainKnowledge" : "Financial markets; Futures; FX", "domainList" : [ "financial-markets", "futures", "fx" ], "domainSpecificKnowledge" : [ "Financial markets", "Futures", "FX" ], "toolProficiency" : [ "Python scientific stack", "Bloomberg Terminal", "Reuters Eikon", "FactSet" ], "communicationSkills" : "Argue concisely; Deal with conflicting views", "problemSolvingSkills" : "Problem solving", "qualificationsBasic" : "4+ years research experience, 4+ years live trading experience, Degree with high mathematical content, Degree with high statistical content, Degree with high computing content", "qualificationsPreferred" : "Experience with intraday predictor design, Experience with monthly predictor design, Experience with portfolio construction, Experience with risk analysis, Understanding of transaction costs, Understanding of mitigation strategies, Ability to mentor junior researchers", "workSiteFlexibility" : "Flexible", "rawDescription" : "About Man Group Man Group is a global alternative investment management firm focused on pursuing outperformance for sophisticated clients via our Systematic, Discretionary and Solutions offerings. Powered by talent and advanced technology, our single and multi-manager investment strategies are underpinned by deep research and span public and private markets, across all major asset classes, with a significant focus on alternatives. Man Group takes a partnership approach to working with clients, establishing deep connections and creating tailored solutions to meet their investment goals and those of the millions of retirees and savers they represent. Headquartered in London, we manage $227.6 billion* and operate across multiple offices globally. Man Group plc is listed on the London Stock Exchange under the ticker EMG.LN and is a constituent of the FTSE 250 Index. Further information can be found at www.man.com * As at 31 December 2025 About Man AHL: Man AHL employs diversified quantitative techniques to offer a range of strategies which encompass traditional momentum, non-traditional momentum, multi-strategy and sector-based approaches. Man AHL’s strategies are primarily alternative and seek to gain potential predictive, alpha-generating insights through rigorous analysis of large data sets. Man AHL is a specialised engine, applying scientific rigour and advanced technology and execution to a diverse range of data to build systematic investment strategies, trading continuously over hundreds of global markets. The team of 150 investment professionals, including 110 researchers, is comprised of scientists, technologists and finance practitioners, driven by curiosity and intellectual honesty, and a passion for solving the complex problems presented by financial markets. The engine leverages Man Group’s unique collaboration with the University of Oxford, the Oxford-Man Institute of Quantitative Finance (OMI). The OMI conducts field-leading academic research into machine learning and data analytics, which can be applied to quantitative investing. Founded in 1987, Man AHL’s funds under management were $63.8 billion at 31 March 2024. Further information can be found at www.man.com/ahl. The Team: AHL Macro is the team responsible for Macro strategies. The team systematically trades liquid futures and FX at different frequencies, with holding periods ranging from monthly to intraday. Technology and Business Skills: 4+ years of experience researching and live trading alpha signals for futures and FX Experience with intraday > monthly predictor design and analysis Experience with portfolio construction, risk analysis Strong understanding of transaction costs, and mitigation strategies Strong coding skills and experience of handling large data sets. We use Python and its scientific stack for both research and live trading Personal Attributes: Strong academic record and a degree with high mathematical, statistical, and computing content e.g., Mathematics, Computer Science, Engineering, Economics or Physics from a leading university Hands-on attitude; willing to get involved with technology and projects across the firm Intellectually robust with a keenly analytic approach to problem solving Self-organised with the ability to effectively manage time across multiple projects and with contending business demands and priorities Strong interpersonal skills; able to build and maintain a close working relationship with quantitative researchers, technologist, traders and senior business stakeholders alike. Ability to mentor junior researchers Confident communicator: able to argue a point concisely and deal positively with conflicting views Working Here: AHL fosters a performance driven, meritocratic culture with a small company, no-attitude feel. It is flat structured, open, transparent, and collaborative, offering ample opportunity to grow and have enormous impact on what we do. We are actively engaged with the broader research and academic community, as well as renowned industry contributors. Inclusion, Work-Life Balance and Benefits at Man Group You'll thrive in our working environment that champions equality of opportunity. Your unique perspective will contribute to our success, joining a workplace where inclusion is fundamental and deeply embedded in our culture and values. Through our external and internal initiatives, partnerships and programmes, you'll find opportunities to grow, develop your talents, and help foster an inclusive environment for all across our firm and industry. Learn more at www.man.com/diversity. You'll have opportunities to make a difference through our charitable and global initiatives, while advancing your career through professional development, and with flexible working arrangements available too. Like all our people, you'll receive two annual 'Mankind' days of paid leave for community volunteering. Our comprehensive benefits package includes competitive holiday entitlements, pension/401k, life and long-term disability coverage, group sick pay, enhanced parental leave and long-service leave. Depending on your location, you may also enjoy additional benefits such as private medical coverage, discounted gym membership options and pet insurance. Equal Employment Opportunity Policy Man Group provides equal employment opportunities to all applicants and all employees without regard to race, color, creed, national origin, ancestry, religion, disability, sex, gender identity and expression, marital status, sexual orientation, military or veteran status, age or any other legally protected category or status in accordance with applicable federal, state and local laws. Man Group is a Disability Confident Committed employer; if you require help or information on reasonable adjustments as you apply for roles with us, please contact TalentAcquisition@man.com.", "summaryDescription" : "Senior Quantitative Researcher - Macro at Man Group. Skills: Quantitative research, Systematic trading, Futures, FX. Research alpha signals. Live trade alpha signals", "postedDate" : "2026-06-13T21:53:56.911", "createdAt" : "2026-06-13T21:53:56.911", "lastUpdated" : "2026-06-15T03:20:54.912", "ingestTimestamp" : "2026-06-13T21:53:56.911", "mongoId" : "6a2c7c2b74d8ee00a094c83a", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "150k-200k", "hasSalary" : false, "allSkills" : [ "Quantitative research", "Systematic trading", "Futures trading", "FX trading", "Data analysis", "Intellectual honesty", "Mentoring", "Analytic approach", "Self-organised", "Interpersonal", "Confident communicator", "Futures", "FX", "Alpha signal research", "Live trading", "Predictor design", "Portfolio construction", "Risk analysis", "Transaction cost analysis", "Data handling", "Financial markets", "Python scientific stack", "Bloomberg Terminal", "Reuters Eikon", "FactSet" ], "skillCount" : 25, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "_score" : 550.2843, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Financial Services", "llmIndustryConfidence" : 0.98 }, { "id" : "68b706957fc9a711f0f6eda5", "title" : "Sr Risk Associate, Risk and Compliance Solutions", "company" : "Amazon Pay (India) Private Limited", "industry" : "Corporate Operations, Risk Family, Retail", "salary" : { "min" : 2200000.0, "max" : 3500000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Risk Associate in FinTech in Bengaluru, India, adjusted for company size and seniority." }, "location" : "Bengaluru, Karnataka, IND", "locations" : [ "Bengaluru, Karnataka, IND" ], "timestamp" : "2026-06-15T09:56:07.645", "fingerprint" : "7326161a1694f4e52f70844cd221efc076f22b400a15dab023643a0a08f73461", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3070457/apply", "externalId" : "622436e1-ee37-4c10-ab98-05c814ccfc59", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Bengaluru", "state" : "Karnataka", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "12.9767936,77.5900820" } ], "locationText" : "Bengaluru, Karnataka, India", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Excel, SQL", "professionalSkills" : [ "Risk management", "Compliance management", "Transaction monitoring", "Regulatory reporting", "Anti money laundering" ], "hardSkillsList" : [ "Suspicious transaction reporting", "Customer risk categorization" ], "hardSkills" : [ { "name" : "Suspicious transaction reporting", "level" : "intermediate" }, { "name" : "Customer risk categorization", "level" : "intermediate" } ], "majorSkills" : "Risk and Compliance, AML transaction monitoring", "majorSkillsList" : [ "Risk and Compliance", "AML transaction monitoring" ], "coreResponsibilities" : "Review potential suspicious transactions, Conduct deep dives, Suspicious transaction reporting templatization, File suspicious transaction reports, Handle inquiries from regulators, Allocate AML trainings, Track AML trainings, Manage customer risk categorization process, Track adherence to AML transaction monitoring process", "domainKnowledge" : "Anti money laundering; Regulatory compliance", "domainList" : [ "anti-money-laundering", "regulatory-compliance" ], "domainSpecificKnowledge" : [ "Anti money laundering", "Regulatory compliance" ], "toolProficiency" : [ "Microsoft Office" ], "documentationSkills" : "Suspicious transaction reporting", "problemSolvingSkills" : "Deep dives", "qualificationsBasic" : "Bachelor's degree, Speak, write, and read fluently in English, Experience with Microsoft Office products and applications, Experience with Excel", "qualificationsPreferred" : "Experience in regulatory compliance management with government agencies, Experience in data-driven business operations processes, SQL knowledge", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Our vision is to make Amazon Pay as the most trusted, convenient and rewarding Payment Experience. Given the highly sensitive nature of Payments business, it is imperative to have robust Risk and Compliance function, to ensure adherence to regulatory compliance and risk management and that's where Risk and Compliance Solutions (RCS) fits in. Risk and Compliance Solutions (RCS) is responsible for operational and compliance risk management for all functions within Amazon Pay. The function is responsible for setting strong operational risk management framework, risk identification, assessment and continuous monitoring framework. In addition, the function also manages key regulatory compliance functions such as regulatory reporting, Anti money laundering program, External Audit engagements, and Governances. This role is for Sr Risk Analyst who will play a critical role in AML transaction monitoring process and will be responsible for review of escalated alerts and filing suspicious transaction reports with the reporting authorities. The incumbent will report directly to the Sr Risk Manager. The Job will entail the following: a. Review of potential suspicious transactions and conducting deep dives b. Suspicious transaction reporting (STR) templatization for onward filing to regulators c. handling of inquiries received from regulators d. allocation and tracking of AML trainings e. managing customer risk categorization process f. tracking adherence to defined AML transaction monitoring process Risk and Compliance continue to evolve and incumbent could be expected to work and manage new programs as per organizational priority. Basic Qualifications: - Bachelor's degree - Speak, write, and read fluently in English - Experience with Microsoft Office products and applications - Experience with Excel Preferred Qualifications: - Experience in regulatory compliance management with government agencies - Experience in data-driven business operations processes - SQL knowledge Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.", "summaryDescription" : "Sr Risk Associate, Risk and Compliance Solutions at Amazon Pay (India) Private Limited. Skills: Risk and Compliance, AML transaction monitoring. Review potential suspicious transactions. Conduct deep dives", "postedDate" : "2026-06-13T15:34:09.574", "createdAt" : "2026-06-13T15:34:09.574", "lastUpdated" : "2026-06-15T09:56:07.645", "ingestTimestamp" : "2026-06-13T15:34:09.574", "mongoId" : "68b706957fc9a711f0f6eda5", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3070457/apply", "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Suspicious transaction reporting", "Customer risk categorization", "Risk and Compliance", "AML transaction monitoring", "Risk management", "Compliance management", "Transaction monitoring", "Regulatory reporting", "Anti money laundering", "Regulatory compliance", "Microsoft Office" ], "skillCount" : 11, "jobCategory" : "operations", "dataQualityScore" : 1.0, "_score" : 543.6834, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Financial Services" }, { "id" : "6a2c5ddf74d8ee00a08df2e2", "title" : "Volatility Quantitative Researcher", "company" : "Walleye Capital", "industry" : "Financial Services", "salary" : { "min" : 120000.0, "max" : 180000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Entry-level Volatility Quantitative Researcher in Miami, adjusted for FinTech industry and company size." }, "location" : "Miami, Florida, United States", "locations" : [ "Miami", "Florida", "United States" ], "timestamp" : "2026-06-14T23:55:42.911", "fingerprint" : "913ba84244eb1b328f599496b7e62d5d8ef5274bbf447a49a54d200859e73a22", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/walleyecapital-external-students/jobs/4586185006", "externalId" : "4586185006", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Miami", "state" : "Florida", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "25.7741566,-80.1935973" } ], "locationText" : "Miami, Florida, United States", "employmentType" : "FULL_TIME", "technicalSkills" : "Python", "professionalSkills" : [ "Quantitative analysis", "Statistical analysis", "Modelling", "Alpha trading strategies", "Portfolio optimization" ], "hardSkillsList" : [ "Time series analysis", "Regression techniques", "Machine learning" ], "hardSkills" : [ { "name" : "Time series analysis", "level" : "intermediate" }, { "name" : "Regression techniques", "level" : "intermediate" }, { "name" : "Machine learning", "level" : "intermediate" } ], "majorSkills" : "Volatility trading, Quantitative research, Machine learning", "majorSkillsList" : [ "Volatility trading", "Quantitative research", "Machine learning" ], "coreResponsibilities" : "Research alpha trading strategies, Design alpha trading strategies, Automate alpha trading strategies, Manipulate proprietary data, Manipulate public data, Build custom data sets, Build predictive models, Monetize trading signals, Manage risk, Automate strategy execution", "teamCollaboration" : "Work with traders; Work with quants; Work with portfolio managers; Work with technology teams", "domainKnowledge" : "Financial instruments; Stocks; Options; Time series financial data", "domainList" : [ "financial-instruments", "stocks", "options", "time-series-financial-data" ], "domainSpecificKnowledge" : [ "Financial instruments", "Stocks", "Options", "Time series financial data" ], "communicationSkills" : "Clarify task requirements; Communicate research findings; Propose solutions", "innovationCreativity" : "Innovate", "problemSolvingSkills" : "Analytical skills", "qualificationsBasic" : "Proficiency in statistical analysis, Modelling of time series financial data, Python required, Basic understanding of financial instruments, Communication skills required, Commitment to thorough, accurate work", "qualificationsPreferred" : "PhD preferred, Specific ML framework experience, Cloud platform certs", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Position: Quantitative Researcher (Full-Time) Location: Miami, Florida Firm Overview Walleye Capital is a ~$16 billion+ multi-strategy investment firm headquartered in New York City, with over 350 employees across five main offices. Founded in 2005 as an options market maker, we have organically grown into a global investment firm specializing in Volatility, Fundamental Equities, and Quant strategies. At Walleye, we continuously innovate by focusing on three core principles: approach, platform, and people. Our approach is to allocate risk capital where we believe there is not only a compelling opportunity, but also a clear ability to define our tangible edge. We seek to leverage the mathematical benefits of diversification while utilizing sophisticated infrastructure, technology, and our balance sheet to do so in a structurally advantageous way. Our platform, developed over two decades, is central to our operations, evolving alongside business complexities and technological advancements to support our team’s success. Our people are our greatest asset, and we’ve cultivated an environment that attracts top talent by balancing autonomy with collaboration, and intelligence with integrity. Quantitative Researcher Walleye Capital is seeking a motivated and technical Quant Researcher to join the Equity Volatility team in Miami. The ideal candidate will possess strong statistical, analytical, and modelling skills. This role offers the opportunity to work with portfolio managers, research, and technology teams to research, design, and automate alpha trading strategies, and completely automate strategy execution. Responsibilities: Work with traders and quants to research, design, and automate alpha trading strategies Manipulate proprietary and public data to build custom data sets for use in research and model development Build predictive models of asset prices over short, medium, and long term frequencies using simple and advanced regression techniques, including machine learning Assist portfolio manager in building portfolio optimization tools to monetize trading signals and manage risk Work with portfolio manager and technology teams to completely automate strategy execution Qualifications: Proficiency in statistical analysis and modelling of time series financial data in Python is required Basic understanding of financial instruments including stocks and options Role is open to new graduates or first-time finance jobs Strong communication skills, such as ability to clarify task requirements, communicate research findings, and propose solutions to challenges are required Commitment to thorough, accurate work Walleye is an equal opportunity employer. Individuals seeking employment are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, sexual orientation, or any other category protected by applicable law. If you require a reasonable accommodation to participate in any part of our hiring process, please contact hr@walleyecapital.com Personal data you provide will be processed in accordance with Walleye Capital LLC’s Privacy Notice available at: https://www.walleyecapital.com/", "summaryDescription" : "Volatility Quantitative Researcher at Walleye Capital. Skills: Volatility trading, Quantitative research, Machine learning. Research alpha trading strategies. Design alpha trading strategies", "postedDate" : "2026-06-12T21:50:45.450", "createdAt" : "2026-06-12T21:50:45.450", "lastUpdated" : "2026-06-14T23:55:42.911", "ingestTimestamp" : "2026-06-12T21:50:45.450", "mongoId" : "6a2c5ddf74d8ee00a08df2e2", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 120000, "salaryAnnualMax" : 180000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Time series analysis", "Regression techniques", "Machine learning", "Volatility trading", "Quantitative research", "Quantitative analysis", "Statistical analysis", "Modelling", "Alpha trading strategies", "Portfolio optimization", "Financial instruments", "Stocks", "Options", "Time series financial data" ], "skillCount" : 14, "jobCategory" : "other", "jobSubcategory" : "single-stock---volatility", "dataQualityScore" : 0.8888889, "_score" : 541.0774, "daysOld" : 2, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Financial Services" }, { "id" : "6a3056cff292fd229cf2f124", "title" : "Senior Product Associate", "company" : "MarketAxess", "industry" : "FinTech", "salary" : { "min" : 120000.0, "max" : 155000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "New York, New York, United States", "locations" : [ "New York", "New York", "United States" ], "timestamp" : "2026-06-16T06:47:59.051", "fingerprint" : "10c1247c77dc08042ff684b3982897b2cdf24508d2630596f2f81f6c72eaf731", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://www.marketaxess.com/careers/current-openings/detail/jobs/4689475006?gh_jid=4689475006", "externalId" : "4689475006", "industryFunction" : { }, "structuredLocations" : [ { "city" : "New York", "state" : "New York", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.7127281,-74.0060152" } ], "locationText" : "New York, New York, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "SQL", "professionalSkills" : [ "Product strategy", "Roadmap development", "User story creation", "Feature prioritization", "Backlog management", "Product performance metrics", "Product ROI analysis" ], "hardSkillsList" : [ "Data analysis", "Market analysis" ], "hardSkills" : [ { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Market analysis", "level" : "intermediate" } ], "majorSkills" : "Product management, Agile development, Fixed income trading", "majorSkillsList" : [ "Product management", "Agile development", "Fixed income trading" ], "coreResponsibilities" : "Partner with Product Manager, Represent business priorities, Define features, Prioritize features, Approve user stories, Maintain communication across stakeholders, Own product backlog, Manage product backlog, Create user stories, Refine user stories, Write user stories, Act as scrum team representative, Engage with stakeholders, Incorporate feedback into roadmap, Drive change, Champion new ideas, Align teams, Motivate teams, Deliver against objectives, Learn quickly, Prioritize backlog of work, Support execution of product strategy, Write user stories with acceptance criteria, Refine user stories with acceptance criteria, Prioritize user stories with acceptance criteria, Ensure delivery of high-quality products, Collaborate with engineering teams, Collaborate with UX teams, Collaborate with business teams, Ensure alignment on feature development, Ensure alignment on technical feasibility, Clarify requirements with developers, Clarify requirements with QA, Troubleshoot issues with developers, Troubleshoot issues with QA, Validate feature completion, Analyze user data, Analyze market data, Produce insightful sales material, Drive product usage, Define product performance metrics, Track product performance metrics, Use data to drive improvements, Showcase progress through demos, Showcase progress through walkthroughs, Support head of product management, Track business KPIs, Measure product ROI, Measure product success, Attend meetings with investor clients, Attend meetings with dealers, Provide product expertise", "teamCollaboration" : "Cross-functional teams; Engineering teams; UX teams; Business teams; Scrum teams; Internal stakeholders; External stakeholders; Investor clients; Dealers", "projectManagementSkills" : [ "Agile delivery techniques", "Sprint planning", "Backlog management", "Iterative development", "Product roadmap" ], "domainKnowledge" : "Fixed income trading; Financial services sector; OMSS API integration; Trading venues; Database design", "domainList" : [ "fixed-income-trading", "financial-services-sector", "omss-api-integration", "trading-venues", "database-design" ], "domainSpecificKnowledge" : [ "Fixed income trading", "Financial services sector", "OMSS API integration", "Trading venues", "Database design" ], "toolProficiency" : [ "Monday.com", "Jira", "Confluence", "MS Office", "Slack", "WebEx" ], "communicationSkills" : "Executive presentations; Product previews", "documentationSkills" : "User stories; Acceptance criteria", "continuousLearning" : "Live learning; On-demand learning; Role-specific training; Lunch and Learns; Guest speakers", "problemSolvingSkills" : "Analytical mindset; Troubleshoot issues", "outcomesObjectives" : "Drive product usage; Drive continuous improvements; Demonstrate value; Demonstrate progress; Measure product ROI; Measure product success", "qualificationsBasic" : "4+ years in product, project, or business analysis, Experience writing user stories, Experience writing acceptance criteria, Experience defining scope of work, Demonstrable ability to work in a team, Experience in Agile delivery techniques, Experience with sprint planning, Experience with backlog management, Experience with iterative development, Experience with Monday.com, Experience with Jira, Experience with Confluence, Experience with MS Office, Experience with Slack, Experience with WebEx, Analytical mindset, Ability to use data to drive product decisions, Ability to improve performance, Experience in financial services sector, Experience in fixed income, Recent experience of OMSS API integration, Fundamental understanding of database design, Working knowledge of SQL, Exposure to API-driven development, Exposure to technical product considerations, Experience with data-driven decision-making, Bachelor's degree in a relevant subject", "qualificationsPreferred" : "Subject matter expert in fixed income trading, Subject matter expert in Agile culture, Subject matter expert in Agile processes, Subject matter expert in Agile practices, Subject matter expert in Agile tooling", "remoteFriendly" : true, "workSiteFlexibility" : "Onsite", "rawDescription" : "About Us MarketAxess is on a journey to digitally transform one of the world’s largest financial markets, enabling the shift from analog, phone-based trading to a fully electronic marketplace. Why does this matter? Because our platform makes trading fixed-income more accessible, ultimately improving transparency, efficiency, and competition in the marketplace. Changing the way an established industry transacts is no easy feat. There will be twists and turns, because no one’s ever done this before. But now, more than 2,000 clients around the world rely on our solutions, and that number is only expected to grow in the years ahead. We know where we’re going. How we get there is up to us. Join us and help Take Us There. The Role This Senior Product Associate role sits within our core trading product team, focused on building the next generation of fixed income trading solutions for clients and dealers. In this role, you will partner closely with the Product Manager to represent business priorities—helping to define and prioritize features, approve user stories, and maintain clear, consistent communication across stakeholders. You will own and manage the product backlog, creating and refining high-quality user stories that are actionable for the scrum team. The Senior Product Associate will also act as a representative of the scrum team when engaging with internal and external stakeholders, ensuring alignment and incorporating feedback into the product roadmap. This role plays a key part in driving change, championing new ideas, and aligning and motivating teams to deliver against shared objectives. How You'll Help Take Us There Learn quickly and become a subject matter expert in both fixed income trading and Agile culture, processes, practices and tooling. Prioritize the backlog of work so that it best supports the execution of the product strategy - write, refine, and prioritize user stories with clear acceptance criteria. Work closely with Product Managers to ensure the delivery of coherent and consistently high-quality products delivered at pace. Collaborate with engineering, UX, and business teams to ensure alignment on feature development and technical feasibility. Work closely with developers and QA to clarify requirements, troubleshoot issues, and validate feature completion. Analyze user and market data for insight on what is driving client behavior. Use this data to produce insightful sales material that will drive product usage. Define and track key product performance metrics, using data to drive continuous improvements. Be comfortable show casing progress to large groups through demos and walkthroughs on topics such as client case studies, user feedback summaries, or product previews to demonstrate value and progress. Support the head of product management in tracking business key performance indicators to measure product ROI/success. Attend meetings with investor clients or dealers and provide product expertise. What We’re Looking for 4+ years working in product, project or business analysis roles. Strong experience writing user stories, acceptance criteria, and defining scope of work for development teams. Demonstrable ability to work in a team environment. Experience in Agile delivery techniques, including sprint planning, backlog management, and iterative development. Hands on experience with tools such as Monday.com, Jira, Confluence, MS Office, Slack, WebEx. Analytical mindset with the ability to use data to drive product decisions and improve performance. Experience in financial services sector/fixed income. Recent experience of OMS/EMS API integration with trading venues. Fundamental understanding of database design, including working knowledge of SQL. Exposure to API-driven development and technical product considerations. Experience with data-driven decision-making Bachelor’s degree in a relevant subject. What You Can Expect from Us Free Food: We provide free lunch for employees when they are working in the office. Plus, our offices are stocked with snacks Paid Time Off: Competitive PTO package including vacation and personal days, sick leave and charity days Generous Parental Leave: Up to 20 weeks fully paid leave 401(k): Dollar-for-dollar employer match up to $17,500 Employee Stock Purchase Plan: Employees can purchase MarketAxess common stock at a discount Wellness Stipend: We provide employees with up to $1K annually towards gym memberships, home office equipment and more Onsite Healthcare: We offer convenient access to world-class care through Mount Sinai at our Hudson Yards location Tuition Assistance and Professional Development: Benefit from live and on-demand learning, role-specific training, employee-led Lunch and Learns and guest speakers Core benefits: Highly competitive medical, dental, and vision programs For job positions in NYC, NY, and other locations where required, the estimated salary range for a new hire into this position is $120,000 USD to $155,000 USD. Actual salary may vary depending on job-related factors, which may include knowledge, skills, experience, and location. You may also be eligible for annual cash incentives, equity, and other benefit programs. MarketAxess Corporation and its affiliates provide equal employment opportunities to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, veteran status, or any other legally protected characteristic in the location in which the candidate is applying. All of your information will be kept confidential according to EEO guidelines. MarketAxess Privacy Notice for Candidates CCPA Notice at Collection for California Employees and Applicants", "summaryDescription" : "Senior Product Associate at MarketAxess. Skills: Product management, Agile development, Fixed income trading. Partner with Product Manager. Represent business priorities", "postedDate" : "2026-06-15T23:22:23.854", "createdAt" : "2026-06-15T23:22:23.854", "lastUpdated" : "2026-06-16T06:47:59.051", "ingestTimestamp" : "2026-06-15T23:22:23.854", "mongoId" : "6a3056cff292fd229cf2f124", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 120000, "salaryAnnualMax" : 155000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Data analysis", "Market analysis", "Product management", "Agile development", "Fixed income trading", "Product strategy", "Roadmap development", "User story creation", "Feature prioritization", "Backlog management", "Product performance metrics", "Product ROI analysis", "Agile delivery techniques", "Sprint planning", "Iterative development", "Product roadmap", "Financial services sector", "OMSS API integration", "Trading venues", "Database design", "Monday.com", "Jira", "Confluence", "MS Office", "Slack", "WebEx" ], "skillCount" : 26, "jobCategory" : "product", "jobSubcategory" : "product_management", "seniorityLevel" : "Senior", "dataQualityScore" : 1.0, "_score" : 540.8108, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2ab6cf74d8ee00a06e1b29", "title" : "Senior Quantitative Treasury & ALM Risk Analyst", "company" : "Ebury", "industry" : "FinTech", "salary" : { "min" : 60000.0, "max" : 85000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Quantitative Treasury & ALM Risk Analyst in Madrid, Spain, adjusted for the FinTech industry and company size." }, "location" : "Madrid", "locations" : [ "Madrid" ], "timestamp" : "2026-06-14T20:28:07.043", "fingerprint" : "48972d2e3042d0bb6ba648b700dd64565ba929bbd3fc0782611403a4497d6ae2", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://ebury.com/company/careers/job?gh_jid=4894996101", "externalId" : "4894996101", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Madrid", "country" : "Spain", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "40.4167820,-3.7035070" } ], "locationText" : "Madrid, Spain", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, NumPy, Pandas, SQL", "professionalSkills" : [ "Quantitative analysis", "Risk modelling", "Data analysis", "Hedging strategies", "Interest rate risk", "IFRS valuation", "Delta attribution", "Pricing strategies", "Revenue optimization" ], "hardSkillsList" : [ "Quantitative modelling", "Liquidity risk simulations", "VaR99 calculations", "Portfolio correlation analysis", "Multi-entity hedging", "Multi-currency hedging", "DV01 analysis", "Code refactoring", "Code optimization" ], "softSkillsList" : [ "Creative thinking", "Innovative thinking", "Analytical skills", "Problem-solving skills", "Curiosity", "Drive to learn" ], "hardSkills" : [ { "name" : "Quantitative modelling", "level" : "intermediate" }, { "name" : "Liquidity risk simulations", "level" : "intermediate" }, { "name" : "VaR99 calculations", "level" : "intermediate" }, { "name" : "Portfolio correlation analysis", "level" : "intermediate" }, { "name" : "Multi-entity hedging", "level" : "intermediate" }, { "name" : "Multi-currency hedging", "level" : "intermediate" }, { "name" : "DV01 analysis", "level" : "intermediate" }, { "name" : "Code refactoring", "level" : "intermediate" }, { "name" : "Code optimization", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Creative thinking" }, { "name" : "Innovative thinking" }, { "name" : "Analytical skills" }, { "name" : "Problem-solving skills" }, { "name" : "Curiosity" }, { "name" : "Drive to learn" } ], "majorSkills" : "Quantitative Treasury, ALM Risk Modelling, Python, SQL", "majorSkillsList" : [ "Quantitative Treasury", "ALM Risk Modelling", "Python", "SQL" ], "coreResponsibilities" : "Assist in development and implementation of quantitative risk, Contribute to simulation of balance sheet evolution, Develop multi-entity, multi-currency hedging strategies, Support mapping of interest rate risk, Automate hedging strategies, Participate in IFRS valuation projects, Participate in delta attribution projects, Link market impacts to revenue drivers, Contribute to refactoring and optimization of code, Assist in analysis of pricing strategies, Assist in analysis of revenue optimization strategies, Document quantitative findings, Present quantitative findings to the team, Brainstorm ideas to innovate current processes", "teamCollaboration" : "Collaborative team environment; Contribute ideas", "domainKnowledge" : "Liquidity risk; Interest rate risk; IFRS valuation; Quantitative finance; Risk modeling", "domainList" : [ "liquidity-risk", "interest-rate-risk", "ifrs-valuation", "quantitative-finance", "risk-modeling" ], "domainSpecificKnowledge" : [ "Liquidity risk", "Interest rate risk", "IFRS valuation", "Quantitative finance", "Risk modeling" ], "toolProficiency" : [ "Python", "SQL" ], "communicationSkills" : "Communication skills; Presentation skills; Explain complex concepts; Confident communication in English", "documentationSkills" : "Documentation", "continuousLearning" : "Drive to learn complex financial concepts", "problemSolvingSkills" : "Problem-solving skills; Analytical skills", "qualificationsBasic" : "+5 years of experience in quantitative analysis or programming, Proficiency in Python, Proficiency in SQL", "qualificationsPreferred" : "Experience in quantitative finance or data analysis would be a plus, Interest and aptitude for quantitative finance and risk modeling", "workSiteFlexibility" : "Onsite", "rawDescription" : "Ebury helps ambitious businesses unlock global growth, and we take the same approach with our people. We encourage innovation and movement, collaboration and problem-solving, and foster an environment where everyone can feel they belong, are valued, supported and empowered to succeed. If you’re a collaborator who wants to help transform how businesses operate globally, get in touch - we’d love to discuss how Ebury can accelerate your career so you can shape the future. Quantitative Treasury/ALM Risk Modelling we redefine them. What you’ll do Assist in the development and implementation of advanced quantitative risk models, including liquidity risk simulations, VaR99 calculations, and portfolio correlation analysis. Contribute to the simulation of balance sheet evolution and the development of multi-entity, multi-currency hedging strategies. Support the mapping of interest rate risk through DV01 analysis and the automation of hedging strategies. Participate in IFRS valuation and delta attribution projects, linking market impacts to revenue drivers. Contribute to the refactoring and optimization of our code using Python and SQL. Assist in the analysis of pricing and revenue optimization strategies. Document and present quantitative findings to the team. Brainstorm and contribute ideas to innovate current processes. What you’ll need +5 years of experience in quantitative analysis or programming. Proficiency in Python (NumPy, Pandas) and SQL. Experience in quantitative finance or data analysis would be a plus. A strong passion for quantitative financial mathematics and quantitative analysis. Creative and innovative thinking, with a desire to challenge existing methodologies. Analytical and problem-solving skills. Communication, documentation and presentation skills with the ability to explain complex concepts clearly and concisely. Curiosity and a drive to learn complex financial concepts. Ability to work effectively in a collaborative team environment. Confident communication in English, both written and spoken. Open to candidates from diverse academic backgrounds, provided they demonstrate a strong interest and aptitude for quantitative finance and risk modeling. Why Ebury? Competitive Starting Salary with an annual discretionary bonus that truly rewards your performance from day one. Dedicated Mentorship: Learn directly from experienced managers who are invested in your success. Cutting-Edge Technology: Leverage state-of-the-art tailor made tools and systems that enable you to perform at your best. Clear, Accelerated Career Progression: Defined pathways to leadership and specialist roles within Ebury. Dynamic & Supportive Culture: Work in a collaborative environment where teamwork and personal growth are prioritized. Generous Benefits Package: Access competitive benefits tailored to your location, which typically include health care and social benefits. Central Malaga Office: A fantastic location with excellent transport links. Ready to launch your career with a global FinTech? Click the ‘Apply’ Today and discover your potential at Ebury! #LI-GC2 #LI-HYBRID About us Ebury delivers sophisticated, integrated solutions — business accounts, hedging, and financing — on a single platform with a seamless workflow. Our success is built on a simple premise and singular purpose: To help businesses operate and scale globally. Since its founding in 2009, Ebury has always been a fast-growing leader in fintech. Today, we bring together 1,800+ Eburians across nearly 70 cities and we’re always looking to add to our team. At the heart of our offering is a proprietary platform, purpose-built to help businesses seamlessly streamline and manage global cash flow. We focus on continuous product evolution and innovation to build the infrastructure for borderless growth and help our clients scale at every stage. The opportunities at Ebury are as diverse as our people, ranging from business development to engineering roles across our tech pillars. We believe in inclusion. We stand against discrimination in all forms and are against the intolerance of differences that makes us a modern and successful organisation. At Ebury, you can be whoever you want to be and still feel a sense of belonging no matter your story.", "summaryDescription" : "Senior Quantitative Treasury & ALM Risk Analyst at Ebury. Skills: Quantitative Treasury, ALM Risk Modelling, Python, SQL. Assist in development and implementation of quantitative risk. Contribute to simulation of balance sheet evolution", "postedDate" : "2026-06-11T21:34:24.503", "createdAt" : "2026-06-11T21:34:24.503", "lastUpdated" : "2026-06-14T20:28:07.043", "ingestTimestamp" : "2026-06-11T21:34:24.503", "mongoId" : "6a2ab6cf74d8ee00a06e1b29", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "50k-75k", "hasSalary" : false, "allSkills" : [ "Quantitative modelling", "Liquidity risk simulations", "VaR99 calculations", "Portfolio correlation analysis", "Multi-entity hedging", "Multi-currency hedging", "DV01 analysis", "Code refactoring", "Code optimization", "Creative thinking", "Innovative thinking", "Analytical skills", "Problem-solving skills", "Curiosity", "Drive to learn", "Quantitative Treasury", "ALM Risk Modelling", "Python", "SQL", "Quantitative analysis", "Risk modelling", "Data analysis", "Hedging strategies", "Interest rate risk", "IFRS valuation", "Delta attribution", "Pricing strategies", "Revenue optimization", "Liquidity risk", "Quantitative finance", "Risk modeling" ], "skillCount" : 31, "jobCategory" : "other", "jobSubcategory" : "treasury", "dataQualityScore" : 0.8888889, "_score" : 538.24603, "daysOld" : 2, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech" }, { "id" : "6a305957f292fd229cf46e46", "title" : "Product Marketing Associate", "company" : "Middesk", "industry" : "Marketing", "salary" : { "min" : 97000.0, "max" : 125000.0, "currency" : "USD", "frequency" : "Yearly" }, "location" : "San Francisco", "locations" : [ "San Francisco" ], "timestamp" : "2026-06-16T14:49:21.289", "fingerprint" : "dfcfd623202523170735286094331bc525986c9e997339d272d5f8f48f94c00e", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/middesk/4f430902-9ff2-4e1c-85ca-258123f3ab0c/application", "externalId" : "4f430902-9ff2-4e1c-85ca-258123f3ab0c", "industryFunction" : { }, "structuredLocations" : [ { "city" : "San Francisco", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "37.7879363,-122.4075201" } ], "locationText" : "San Francisco, California, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 3, "experienceMaxYears" : 5, "experienceLevel" : "Mid", "technicalSkills" : "AI-enabled marketing", "professionalSkills" : [ "Product marketing", "Content marketing", "B2B marketing", "GTM launch execution", "Sales enablement", "Competitive positioning", "Messaging" ], "hardSkillsList" : [ "Customer research", "Feedback synthesis", "Usage data analysis" ], "softSkillsList" : [ "Ownership mentality", "Ambiguity", "Building" ], "hardSkills" : [ { "name" : "Customer research", "level" : "intermediate" }, { "name" : "Feedback synthesis", "level" : "intermediate" }, { "name" : "Usage data analysis", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Ownership mentality" }, { "name" : "Ambiguity" }, { "name" : "Building" } ], "majorSkills" : "Product marketing, Go-to-market, Sales enablement, Competitive intelligence", "majorSkillsList" : [ "Product marketing", "Go-to-market", "Sales enablement", "Competitive intelligence" ], "coreResponsibilities" : "Support product marketing initiatives, Execute product marketing initiatives, Contribute to positioning, Contribute to launch execution, Contribute to sales enablement, Contribute to competitive intelligence, Develop positioning and messaging, Execute go-to-market launches, Create sales enablement materials, Track competitive intelligence, Conduct customer research, Synthesize feedback, Analyze usage data, Distribute product stories, Distribute Middesk's point of view", "teamCollaboration" : "Work with product teammates; Work with sales teammates; Work with marketing teammates; Work across sales; Work across product; Work across marketing", "domainKnowledge" : "Business identity products; Fintech; Lenders; Marketplaces; Financial services; Compliance; Identity; Financial services use cases", "domainList" : [ "business-identity-products", "fintech", "lenders", "marketplaces", "financial-services", "compliance", "identity", "financial-services-use-cases" ], "domainSpecificKnowledge" : [ "Business identity products", "Fintech", "Lenders", "Marketplaces", "Financial services", "Compliance", "Identity", "Financial services use cases" ], "communicationSkills" : "Translating complex products; Clear messaging; Audience-ready messaging", "specialRequirements" : "2 days per week in SF office, Based within commutable distance", "qualificationsBasic" : "3+ years in product marketing, 3+ years in content marketing, 3+ years in B2B marketing, Hands-on experience with AI-enabled marketing workflows, Familiarity with GTM launch execution, Familiarity with sales enablement, Familiarity with competitive positioning, Written communication skills, High ownership mentality, Comfortable operating with ambiguity, Motivated by building", "qualificationsPreferred" : "Experience at high-growth fintech, Experience at B2B SaaS company, Exposure to compliance use cases, Exposure to identity use cases, Exposure to financial services use cases", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "ABOUT MIDDESK: Middesk makes it easier for businesses to work together. Since 2018, we’ve been transforming business identity verification, replacing slow, manual processes with seamless access to complete, up-to-date data. Our platform helps companies across industries confidently verify business identities, onboard customers faster, and reduce risk at every stage of the customer lifecycle. Middesk came out of Y Combinator, is backed by Sequoia Capital and Accel Partners, and was recently named to Forbes Fintech 50 List. ABOUT THE ROLE: We're looking for a Product Marketing Associate to support and execute product marketing initiatives across the full GTM lifecycle. This is a great role for someone who's ready to own real work, not just assist on it, and grow their craft in a fast-moving environment. You'll contribute to positioning, launch execution, sales enablement, and competitive intelligence, working closely with product, sales, and marketing teammates. You're comfortable taking a clear brief and running with it, you ask good questions when direction is ambiguous, and you care about doing the work well. This role is a fit for someone building toward a broader PMM scope where you'll have real ownership from day one, and room to grow into more strategic territory as you develop. We follow a hybrid work model, and for this role, there is an expectation of 2 days per week in our SF office. Candidates should be based within a commutable distance, as we believe in the value of in-person collaboration and building strong team connections while also supporting flexibility where possible. WHAT YOU'LL DO: - Positioning and messaging for our business identity products across key segments including fintechs, lenders, enterprise financial services, and marketplaces - Go-to-market execution for new product and feature launches, from coordinating across teams to hitting milestones from beta through release - Sales enablement materials including pitch decks, one-pagers, and competitive battle cards that help the sales team move deals forward - Competitive intelligence tracking to keep our frameworks current and our team equipped to win - Customer research in partnership with senior teammates – interviews, feedback synthesis, and usage data – that sharpens our messaging and informs GTM decisions - Distribution of product stories and Middesk's point of view in market, in coordination with the broader marketing team WHAT WE'RE LOOKING FOR: - 3+ years in product marketing, content marketing, or a related B2B marketing role - Hands-on experience with AI-enabled marketing workflows, and genuine curiosity about how AI is changing the way buyers discover and evaluate products - Familiarity with GTM launch execution, sales enablement, or competitive positioning - Strong written communication skills and an instinct for translating complex products into clear, audience-ready messaging - High ownership mentality – you follow through, communicate proactively, and care about the outcome, not just the task - Comfortable operating with some ambiguity and motivated by building rather than inheriting - Collaborative by default, with a track record of working well across sales, product, and marketing teams NICE-TO-HAVE: - Experience at a high-growth fintech or B2B SaaS company - Exposure to compliance, identity, or financial services use cases", "summaryDescription" : "Product Marketing Associate at Middesk. Skills: Product marketing, Go-to-market, Sales enablement, Competitive intelligence. Support product marketing initiatives. Execute product marketing initiatives", "createdAt" : "2026-06-16T00:25:11.335", "lastUpdated" : "2026-06-16T14:49:21.289", "ingestTimestamp" : "2026-06-16T00:25:11.335", "mongoId" : "6a305957f292fd229cf46e46", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 97000, "salaryAnnualMax" : 125000, "salaryBand" : "75k-100k", "hasSalary" : true, "allSkills" : [ "Customer research", "Feedback synthesis", "Usage data analysis", "Ownership mentality", "Ambiguity", "Building", "Product marketing", "Go-to-market", "Sales enablement", "Competitive intelligence", "Content marketing", "B2B marketing", "GTM launch execution", "Competitive positioning", "Messaging", "Business identity products", "Fintech", "Lenders", "Marketplaces", "Financial services", "Compliance", "Identity", "Financial services use cases" ], "skillCount" : 23, "jobCategory" : "marketing", "jobSubcategory" : "growth", "seniorityLevel" : "Mid", "dataQualityScore" : 0.8888889, "_score" : 534.7763, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2a524a74d8ee00a05f9584", "title" : "Senior Quantitative Treasury & ALM Risk Analyst", "company" : "Ebury", "industry" : "FinTech", "salary" : { "min" : 65000.0, "max" : 90000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Quantitative Treasury & ALM Risk Analyst in Madrid, Spain, adjusted for the FinTech industry and company size." }, "location" : "Madrid", "locations" : [ "Madrid" ], "timestamp" : "2026-06-14T10:05:50.118", "fingerprint" : "b993c775a65d4aac7ff81eef477c15967211fdc9a21aaef38a632ea995c221d8", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://ebury.com/company/careers/job?gh_jid=4890238101", "externalId" : "4890238101", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Madrid", "country" : "Spain", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "40.4167820,-3.7035070" } ], "locationText" : "Madrid, Spain", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, NumPy, Pandas, SQL", "professionalSkills" : [ "Quantitative analysis", "Risk modelling", "Balance sheet evolution", "Hedging strategies", "Interest rate risk", "IFRS valuation", "Delta attribution", "Pricing strategies", "Revenue optimization" ], "hardSkillsList" : [ "Quantitative modelling", "Liquidity risk simulations", "VaR99 calculations", "Portfolio correlation analysis", "DV01 analysis", "Code refactoring", "Code optimization" ], "softSkillsList" : [ "Creative thinking", "Innovative thinking", "Analytical skills", "Problem-solving skills", "Curiosity", "Drive to learn" ], "hardSkills" : [ { "name" : "Quantitative modelling", "level" : "intermediate" }, { "name" : "Liquidity risk simulations", "level" : "intermediate" }, { "name" : "VaR99 calculations", "level" : "intermediate" }, { "name" : "Portfolio correlation analysis", "level" : "intermediate" }, { "name" : "DV01 analysis", "level" : "intermediate" }, { "name" : "Code refactoring", "level" : "intermediate" }, { "name" : "Code optimization", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Creative thinking" }, { "name" : "Innovative thinking" }, { "name" : "Analytical skills" }, { "name" : "Problem-solving skills" }, { "name" : "Curiosity" }, { "name" : "Drive to learn" } ], "majorSkills" : "Quantitative Treasury, ALM Risk Modelling, Python, SQL", "majorSkillsList" : [ "Quantitative Treasury", "ALM Risk Modelling", "Python", "SQL" ], "coreResponsibilities" : "Assist in development and implementation of quantitative risk, Contribute to simulation of balance sheet evolution, Contribute to development of hedging strategies, Support mapping of interest rate risk, Support automation of hedging strategies, Participate in IFRS valuation projects, Participate in delta attribution projects, Contribute to refactoring code, Contribute to optimization of code, Assist in analysis of pricing strategies, Assist in analysis of revenue optimization strategies, Document quantitative findings, Present quantitative findings, Brainstorm ideas to innovate processes", "teamCollaboration" : "Collaborative team environment", "domainKnowledge" : "Liquidity risk; Interest rate risk; IFRS valuation; Quantitative finance; Risk modeling", "domainList" : [ "liquidity-risk", "interest-rate-risk", "ifrs-valuation", "quantitative-finance", "risk-modeling" ], "domainSpecificKnowledge" : [ "Liquidity risk", "Interest rate risk", "IFRS valuation", "Quantitative finance", "Risk modeling" ], "communicationSkills" : "Documentation; Presentation; Explain complex concepts", "documentationSkills" : "Documentation", "continuousLearning" : "Learn complex financial concepts", "problemSolvingSkills" : "Analytical skills; Problem-solving skills", "qualificationsBasic" : "+5 years of experience in quantitative analysis or programming, Proficiency in Python, Proficiency in SQL, Confident communication in English", "qualificationsPreferred" : "Experience in quantitative finance, Experience in data analysis, Interest and aptitude for quantitative finance, Interest and aptitude for risk modeling", "workSiteFlexibility" : "Onsite", "rawDescription" : "Ebury helps ambitious businesses unlock global growth, and we take the same approach with our people. We encourage innovation and movement, collaboration and problem-solving, and foster an environment where everyone can feel they belong, are valued, supported and empowered to succeed. If you’re a collaborator who wants to help transform how businesses operate globally, get in touch - we’d love to discuss how Ebury can accelerate your career so you can shape the future. Quantitative Treasury/ALM Risk Modelling we redefine them. What you’ll do Assist in the development and implementation of advanced quantitative risk models, including liquidity risk simulations, VaR99 calculations, and portfolio correlation analysis. Contribute to the simulation of balance sheet evolution and the development of multi-entity, multi-currency hedging strategies. Support the mapping of interest rate risk through DV01 analysis and the automation of hedging strategies. Participate in IFRS valuation and delta attribution projects, linking market impacts to revenue drivers. Contribute to the refactoring and optimization of our code using Python and SQL. Assist in the analysis of pricing and revenue optimization strategies. Document and present quantitative findings to the team. Brainstorm and contribute ideas to innovate current processes. What you’ll need +5 years of experience in quantitative analysis or programming. Proficiency in Python (NumPy, Pandas) and SQL. Experience in quantitative finance or data analysis would be a plus. A strong passion for quantitative financial mathematics and quantitative analysis. Creative and innovative thinking, with a desire to challenge existing methodologies. Analytical and problem-solving skills. Communication, documentation and presentation skills with the ability to explain complex concepts clearly and concisely. Curiosity and a drive to learn complex financial concepts. Ability to work effectively in a collaborative team environment. Confident communication in English, both written and spoken. Open to candidates from diverse academic backgrounds, provided they demonstrate a strong interest and aptitude for quantitative finance and risk modeling. Why Ebury? Competitive Starting Salary with an annual discretionary bonus that truly rewards your performance from day one. Dedicated Mentorship: Learn directly from experienced managers who are invested in your success. Cutting-Edge Technology: Leverage state-of-the-art tailor made tools and systems that enable you to perform at your best. Clear, Accelerated Career Progression: Defined pathways to leadership and specialist roles within Ebury. Dynamic & Supportive Culture: Work in a collaborative environment where teamwork and personal growth are prioritized. Generous Benefits Package: Access competitive benefits tailored to your location, which typically include health care and social benefits. Central Madrid Office: A fantastic location with excellent transport links. Ready to launch your career with a global FinTech? Click the ‘Apply’ Today and discover your potential at Ebury! #LI-GC2 #LI-HYBRID About us Ebury delivers sophisticated, integrated solutions — business accounts, hedging, and financing — on a single platform with a seamless workflow. Our success is built on a simple premise and singular purpose: To help businesses operate and scale globally. Since its founding in 2009, Ebury has always been a fast-growing leader in fintech. Today, we bring together 1,800+ Eburians across nearly 70 cities and we’re always looking to add to our team. At the heart of our offering is a proprietary platform, purpose-built to help businesses seamlessly streamline and manage global cash flow. We focus on continuous product evolution and innovation to build the infrastructure for borderless growth and help our clients scale at every stage. The opportunities at Ebury are as diverse as our people, ranging from business development to engineering roles across our tech pillars. We believe in inclusion. We stand against discrimination in all forms and are against the intolerance of differences that makes us a modern and successful organisation. At Ebury, you can be whoever you want to be and still feel a sense of belonging no matter your story.", "summaryDescription" : "Senior Quantitative Treasury & ALM Risk Analyst at Ebury. Skills: Quantitative Treasury, ALM Risk Modelling, Python, SQL. Assist in development and implementation of quantitative risk. Contribute to simulation of balance sheet evolution", "postedDate" : "2026-06-11T20:18:03.651", "createdAt" : "2026-06-11T20:18:03.651", "lastUpdated" : "2026-06-14T10:05:50.118", "ingestTimestamp" : "2026-06-11T20:18:03.651", "mongoId" : "6a2a524a74d8ee00a05f9584", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "50k-75k", "hasSalary" : false, "allSkills" : [ "Quantitative modelling", "Liquidity risk simulations", "VaR99 calculations", "Portfolio correlation analysis", "DV01 analysis", "Code refactoring", "Code optimization", "Creative thinking", "Innovative thinking", "Analytical skills", "Problem-solving skills", "Curiosity", "Drive to learn", "Quantitative Treasury", "ALM Risk Modelling", "Python", "SQL", "Quantitative analysis", "Risk modelling", "Balance sheet evolution", "Hedging strategies", "Interest rate risk", "IFRS valuation", "Delta attribution", "Pricing strategies", "Revenue optimization", "Liquidity risk", "Quantitative finance", "Risk modeling" ], "skillCount" : 29, "jobCategory" : "other", "jobSubcategory" : "treasury", "dataQualityScore" : 0.8888889, "_score" : 534.3559, "daysOld" : 2, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech" }, { "id" : "69ec72c64c40e2acd1d0b24c", "title" : "Internship – Quantitative Energy Systems Analysis", "company" : "IAEA", "location" : "Austria-Vienna-Vienna-IAEA Headquarters", "locations" : [ "Austria-Vienna-Vienna-IAEA Headquarters", "2026-05-15, 11:59:00 PM" ], "timestamp" : "2026-06-15T10:02:48.469", "fingerprint" : "bb72c96de45dc5683c6e647989132f626e7c5823a392cd14aef09ed094837d15", "source" : "taleo", "applyUrl" : "https://iaea.taleo.net/careersection/ex/jobdetail.ftl?job=1307811", "externalId" : "1307811", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Vienna", "country" : "Austria", "continent" : "eu", "source" : "llm", "workMode" : "onsite" } ], "locationText" : "Vienna, Austria", "employmentType" : "INTERNSHIP", "experienceMinYears" : 0, "experienceMaxYears" : 1, "experienceLevel" : "Entry", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "NEPIK-Planning and Economic Studies Section Austria-Vienna-Vienna-IAEA Headquarters", "summaryDescription" : "Internship – Quantitative Energy Systems Analysis at IAEA", "createdAt" : "2026-06-14T19:48:54.620", "lastUpdated" : "2026-06-15T10:02:48.469", "ingestTimestamp" : "2026-06-14T19:48:54.620", "mongoId" : "69ec72c64c40e2acd1d0b24c", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Entry", "dataQualityScore" : 0.6666667, "_score" : 530.39825, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Government", "llmIndustryConfidence" : 0.9 }, { "id" : "69f519c94c40e2acd1eb1bfe", "title" : "Sr. Financial Analyst, Sponsored Products and Brands Finance", "company" : "Amazon.com Services LLC", "industry" : "Finance Accounting, Finance/Planning, finance", "salary" : { "min" : 60000.0, "max" : 128800.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "New York, New York, USA", "locations" : [ "New York, New York, USA" ], "certifications" : [ "CFA", "CPA", "FRM", "Series 7", "Series 63", "Series 65" ], "timestamp" : "2026-06-15T05:14:03.572", "fingerprint" : "b87718796df4c362e547a1b03b9638333f3b51df660eee53f704be3c1e0c147d", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10408978/apply", "externalId" : "f29b5d25-6d4b-4926-9e38-a94ff1bfe861", "industryFunction" : { }, "structuredLocations" : [ { "city" : "New York", "state" : "New York", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.7127281,-74.0060152" } ], "locationText" : "New York, New York, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 3, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, R, MATLAB, SQL", "professionalSkills" : [ "Financial modeling", "Risk management", "Quantitative analysis" ], "hardSkillsList" : [ "Financial analysis", "Data analysis", "Statistical modeling" ], "hardSkills" : [ { "name" : "Financial analysis", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Statistical modeling", "level" : "intermediate" } ], "majorSkills" : "Financial analysis, Risk management, Quantitative skills", "majorSkillsList" : [ "Financial analysis", "Risk management", "Quantitative skills" ], "coreResponsibilities" : "Analyze financial data, Develop financial models, Assess financial risks, Monitor market trends, Prepare financial reports, Ensure regulatory compliance, Collaborate with stakeholders", "teamCollaboration" : "Cross-functional teams; Finance department", "domainKnowledge" : "Financial instruments; Regulatory frameworks; Risk methodologies; SOX; Basel III; MiFID II; Dodd-Frank; FINRA; SEC; FCA; GDPR; AML/KYC; Equities; Fixed income; Derivatives; FX; Structured products; Private credit; VaR; CVaR; Stress testing; Monte Carlo; Factor models; Credit scoring", "domainList" : [ "financial-instruments", "regulatory-frameworks", "risk-methodologies", "sox", "basel-iii", "mifid-ii", "dodd-frank", "finra", "sec", "fca", "gdpr", "aml-kyc", "equities", "fixed-income", "derivatives", "fx", "structured-products", "private-credit", "var", "cvar", "stress-testing", "monte-carlo", "factor-models", "credit-scoring" ], "domainSpecificKnowledge" : [ "Financial instruments", "Regulatory frameworks", "Risk methodologies", "SOX", "Basel III", "MiFID II", "Dodd-Frank", "FINRA", "SEC", "FCA", "GDPR", "AML/KYC", "Equities", "Fixed income", "Derivatives", "FX", "Structured products", "Private credit", "VaR", "CVaR", "Stress testing", "Monte Carlo", "Factor models", "Credit scoring" ], "toolProficiency" : [ "Bloomberg Terminal", "Reuters Eikon", "FactSet", "Murex", "Calypso" ], "communicationSkills" : "Report writing; Presentation skills", "problemSolvingSkills" : "Analytical skills", "qualificationsBasic" : "3+ years experience", "qualificationsPreferred" : "CFA charterholder preferred, CPA preferred, FRM preferred, Series 7 preferred, Series 63 preferred, Series 65 preferred, Bloomberg Terminal proficiency preferred, Reuters Eikon proficiency preferred, FactSet proficiency preferred, Murex proficiency preferred, Calypso proficiency preferred", "remoteFriendly" : false, "workSiteFlexibility" : "onsite", "rawDescription" : "As a Sr. Financial Analyst in the Sponsored Products finance organization, you will be a key member of the Sponsored Products advertising team. You will work side by side with product and finance leaders to develop business strategies, financial models and analytical insights that influence business decisions. As a finance partner, you will have the opportunity to work with large advertising data sets to influence the long-term evolution of our products and develop insights into various aspects of our business. Key job responsibilities Responsibilities include, but are not limited to: Serve as a finance partner for the SP product and engineering leaders on strategic initiatives, leading planning, business modeling, and financial analysis; Design and develop performance metrics, institute reporting mechanisms, and implement processes to drive insights related to business performance for stakeholders; Facilitate financial and operational metrics review meetings with product and finance leaders and work with business to drive effective execution; Develop financial models for new business initiatives, experimentation, and special projects; Collaborate with business intelligence engineers and data engineers to continually improve and enhance existing reporting and mechanisms, proactively identify performance issues and deep dive to investigate and uncover insights; A day in the life A day in the life of a Sr. Financial Analyst can include - leading a WBR to drive discussions with product teams on business performance, partner with product to investigate KPI trends and prepare a document to be reviewed with senior product leaders, collaborate with BIE and Data Engineering teams to design and implement a new set of metrics in multiple formats (WBR/MBR slides, dashboards) for business stakeholders. About the team Sponsored Products (SP) Advertising is one of the largest and fast growing business segments within Amazon Advertising. The SPB Finance team partners with this business to provide data analytics and reporting, support product initiative launches and performance tracking, drive operational improvements, and deep dive into business performance to provide insights that can enable growth. Basic Qualifications: - 3+ years of tax, finance or a related analytical field experience - 4+ years of Accounts Receivable or Account Payable experience - 4+ years of applying key financial performance indicators (KPIs) to analyses experience - 4+ years of creating process improvements with automation and analysis experience - 4+ years of identifying, leading, and executing opportunities to improve, automate, standardize or simplify finance or business tools and processes experience - Bachelor's degree in engineering, statistics or business, or Bachelor's degree and 5+ years of quantitative role (engineering, process re-engineering, quality assurance) experience - Six Sigma Black Belt - Experience with advanced use of SQL for data mining and business intelligence - Experience as a lean sensei, or experience working as a Quality Assurance Engineer Preferred Qualifications: - 4+ years of participating in continuous improvement projects in your team to scale and improve controllership with measurable results experience - MBA, or CPA - Knowledge of Tableau - Experience working with large-scale data mining and reporting tools (examples: SQL, MS Access, Essbase, Cognos) and other financial systems (examples: Oracle, SAP, Lawson, JD Edwards) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, NY, New York - 73,600.00 - 128,800.00 USD annually USA, WA, SEATTLE - 82,700.00 - 117,100.00 USD annually", "summaryDescription" : "Sr. Financial Analyst, Sponsored Products and Brands Finance at Amazon.com Services LLC. Skills: Financial analysis, Risk management, Quantitative skills. Analyze financial data. Develop financial models", "postedDate" : "2026-06-13T18:24:01.965", "createdAt" : "2026-06-13T18:24:01.965", "lastUpdated" : "2026-06-15T05:14:03.572", "ingestTimestamp" : "2026-06-13T18:24:01.965", "mongoId" : "69f519c94c40e2acd1eb1bfe", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10408978/apply", "salaryAnnualMin" : 60000, "salaryAnnualMax" : 128800, "salaryBand" : "50k-75k", "hasSalary" : true, "allSkills" : [ "Financial analysis", "Data analysis", "Statistical modeling", "Risk management", "Quantitative skills", "Financial modeling", "Quantitative analysis", "Financial instruments", "Regulatory frameworks", "Risk methodologies", "SOX", "Basel III", "MiFID II", "Dodd-Frank", "FINRA", "SEC", "FCA", "GDPR", "AML/KYC", "Equities", "Fixed income", "Derivatives", "FX", "Structured products", "Private credit", "VaR", "CVaR", "Stress testing", "Monte Carlo", "Factor models", "Credit scoring", "CFA", "CPA", "FRM", "Series 7", "Series 63", "Series 65", "Bloomberg Terminal", "Reuters Eikon", "FactSet", "Murex", "Calypso" ], "skillCount" : 42, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Senior", "dataQualityScore" : 1.0, "_score" : 529.8687, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "E-Commerce", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c618a74d8ee00a08f4d01", "title" : "Senior Quantitative Risk Analyst", "company" : "Statkraft", "industry" : "Renewables And Environment", "location" : "Oslo, Oslo County, NO", "locations" : [ "Oslo", "Oslo County", "NO" ], "timestamp" : "2026-06-15T10:26:08.321", "fingerprint" : "419eea1c5335219c77922ffec28a95fe84f4fe808954c0399b556d04de230ee8", "source" : "smartrecruiters", "applyUrl" : "https://jobs.smartrecruiters.com/Statkraft1/744000131481869-senior-quantitative-risk-analyst-m-f-d-renewable-energy", "externalId" : "744000131481869", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Oslo", "state" : "Oslo County", "country" : "Norway", "continent" : "eu", "source" : "llm", "workMode" : "onsite" } ], "locationText" : "Oslo, Oslo County, Norway", "employmentType" : "FULL_TIME", "minimumEducation" : "Master", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "mid", "technicalSkills" : "Python", "professionalSkills" : [ "commodity markets, energy markets, PPAs, BESS contracts" ], "hardSkillsList" : [ "risk modelling", "valuation", "stochastic processes", "fundamental models" ], "softSkillsList" : [ "team player, integrity" ], "hardSkills" : [ { "name" : "risk modelling", "level" : "intermediate" }, { "name" : "valuation", "level" : "intermediate" }, { "name" : "stochastic processes", "level" : "intermediate" }, { "name" : "fundamental models", "level" : "intermediate" } ], "softSkills" : [ { "name" : "team player, integrity" } ], "majorSkills" : "quantitative modelling, risk modelling, Python, commodity markets", "majorSkillsList" : [ "quantitative modelling, risk modelling, Python, commodity markets" ], "coreResponsibilities" : "Lead the development of risk and valuation models for physical and financial energy assets, options trading, and non-standard long-term contracts such as PPAs or BESS contracts. Calibrate stochastic price simulation models and be at the forefront of combining fundamental analysis with quantitative risk modelling. Provide guidance and drive best practices in quantitative risk modelling and analytics to deliver robust risk tools. Collaborate closely with stakeholders in the Risk department and Front Office teams. Actively support the conversion of model prototypes into usable daily risk tools through close collaboration with IT.", "teamCollaboration" : "Collaborate closely with stakeholders in the Risk department and Front Office teams. Actively support the conversion of model prototypes into usable daily risk tools through close collaboration with IT.", "communicationSkills" : "communicate complex topics clearly", "continuousLearning" : "Unlimited learning opportunities at various levels of the organisation. The chance to grow your career alongside a truly global network of experts, leaders, specialists and graduates from different countries and backgrounds.", "problemSolvingSkills" : "risk analysis; valuation; quantitative modelling", "specialRequirements" : "Background checks on qualified applicants before hire. This may include a conflicts of interest statement from candidates.", "outcomesObjectives" : "Ensure that our risk measurement is aligned with Statkraft’s Market Operation's needs, as well as changes in the energy markets. Deliver robust risk tools. Contribute to a more sustainable future.", "qualificationsBasic" : "Master’s degree in a quantitative field such as mathematics, economics, physics, or engineering. Several years of experience in quantitative modelling of commodity markets, with a focus on valuation, risk modelling, stochastic processes, and/or fundamental models. Programming skills in Python or a comparable language. A highly structured and solution-oriented work approach. A proactive team player with integrity and the ability to communicate complex topics clearly across the organization. Fluency in English, both written and spoken.", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Statkraft has been making clean energy possible for over a century. Unrivaled pioneering spirit and a strong commitment towards a more sustainable future. That’s what we offer. Today, we are Europe’s largest renewable energy producer and employ more than 7.000 colleagues in 20+ countries around the world. Our vision is clear - to renew the way the world is powered. But there is more work to be done and that is why we need you to help us! Why join us We promise, that here with us, you will build a better way. You will take ownership for projects, you will collaborate across boundaries, you will embrace new skills, guide and be surrounded by some of the smartest people in the industry. Together we lead the energy transition to ensure a more sustainable future for our customers, society and future generations. Together, let’s renew the way the world is powered by building a better way. As a Senior Quantitative Risk Analyst (m/f/d), you will deliver high-quality risk modelling solutions to the Risk department and ensure that our risk measurement is aligned with Statkraft’s Market Operation's needs, as well as changes in the energy markets. You will: * Lead the development of risk and valuation models for physical and financial energy assets, options trading, and non-standard long-term contracts such as PPAs or BESS contracts * Calibrate stochastic price simulation models and be at the forefront of combining fundamental analysis with quantitative risk modelling * Provide guidance and drive best practices in quantitative risk modelling and analytics to deliver robust risk tools * Collaborate closely with stakeholders in the Risk department and Front Office teams * Actively support the conversion of model prototypes into usable daily risk tools through close collaboration with IT ## Qualifications We look for a Senior Quantitative Risk Analyst (m/f/d) with the skills required to strengthen our quantitative risk modelling capabilities for Market Operations. That includes: * Master’s degree in a quantitative field such as mathematics, economics, physics, or engineering * Several years of experience in quantitative modelling of commodity markets, with a focus on valuation, risk modelling, stochastic processes, and/or fundamental models * Strong programming skills in Python or a comparable language * A highly structured and solution-oriented work approach * A proactive team player with strong integrity and the ability to communicate complex topics clearly across the organization * Fluency in English, both written and spoken ## Additional Information At Statkraft, you’ll shape a career that is truly forward-facing with many amazing opportunities and offerings to match. This includes (non-exclusive): * Unlimited learning opportunities at various levels of the organisation * The chance to grow your career alongside a truly global network of experts, leaders, specialists and graduates from different countries and backgrounds. * The opportunity to work somewhere with pride, and to be able to honestly say “My work is contributing to saving the planet”. * A work culture that puts emphasis on the individual, offering flexible working solutions, and work life balance principles. Our vision is to renew the way the world is powered. To navigate the complex journey ahead, we need every voice at the table. We therefore work actively to be a diverse and inclusive workplace and welcome all applicants regardless of background, gender, age, sexual orientation, religious belief, ethnicity, nationality or disability. Statkraft offers competitive terms of employment and benefits schemes, and we’re a trusted employer that puts the safety of our people first. We believe that a safe and healthy working environment is a matter of choice, not chance. Statkraft manages critical infrastructure and services in several countries. We conduct background checks on qualified applicants before hire. This may include a conflicts of interest statement from candidates.", "summaryDescription" : "Senior Quantitative Risk Analyst at Statkraft. Skills: quantitative modelling, risk modelling, Python, commodity markets. Lead the development of risk and valuation models for physical and financial energy assets, options trading, and non-standard long-term contracts such as PPAs or BESS contracts. Calibrate stochastic price simulation models and be at the forefront of combining fundamental analysis with quantitative risk modelling. Provide guidance and drive best practices in quantitative risk ", "postedDate" : "2026-06-10T15:09:50.000", "createdAt" : "2026-06-14T21:41:39.705", "lastUpdated" : "2026-06-15T10:26:08.321", "ingestTimestamp" : "2026-06-14T21:41:39.705", "mongoId" : "6a2c618a74d8ee00a08f4d01", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "hasSalary" : false, "allSkills" : [ "risk modelling", "valuation", "stochastic processes", "fundamental models", "team player, integrity", "quantitative modelling, risk modelling, Python, commodity markets", "commodity markets, energy markets, PPAs, BESS contracts" ], "skillCount" : 7, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "_score" : 528.92065, "daysOld" : 4, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Climate Tech", "llmIndustryConfidence" : 0.95 } ], "status" : 200, "message" : "OK", "pagination" : { "page" : 0, "limit" : 50, "totalCount" : 83701, "totalPages" : 1675, "hasNext" : true, "hasPrevious" : false } }

Quantitative Aspects Of The Products And Associated Risks Jobs in Austin

Senior Quantitative Risk Strategist

Quantitative Analyst - Risk

Product Analyst, Quantitative Equities

Quantitative Product Development Engineer

Quantitative Developer

Quantitative Developer

Quantitative Trader

Quantitative Researcher

Sr. Quantitative Modeler

Associate/AVP, Quantitative Strategies Group

Graduate Quantitative Researcher

Senior Product Quantitative Researcher, Cloud Security

Quantitative Research Intern

Associate Risk Engineer (Underwriter), Executive Risks

Quantitative Equity Analyst

Quantitative Equity Analyst

Quantitative Data Analyst

Shariah Risk Associate

Experienced Quantitative Researcher

Quantitative Researcher - Macro Assets

Quantitative Portfolio Implementation Analyst

Quantitative Research Analyst

Junior Quantitative Researcher

Senior Quantitative Developer

Postdoctoral Fellow - Computational and Quantitative Medicine

Junior Quantitative Researcher

Quantitative Developer, Intern

Quantitative Trading Strategist

Director (Regulation and Prequalification of Medicines and Health Products)

Quantitative UX Researcher

Sr Risk Associate

Associate Director, Quantitative Research

Associate Director, Quantitative Research

Associate Director, Information Security Risk

VP of Financial Products & Marketplace

Associate Director, Information Security Risk

Quantitative Researcher for Risk and Research Engagement

Quantitative Researcher - Deep Learning

Senior Project Manager, Quantitative Research

Senior Quantitative Treasury & ALM Risk Analyst

Senior Quantitative Researcher - Macro

Sr Risk Associate, Risk and Compliance Solutions

Volatility Quantitative Researcher

Senior Product Associate

Senior Quantitative Treasury & ALM Risk Analyst

Product Marketing Associate

Senior Quantitative Treasury & ALM Risk Analyst

Internship – Quantitative Energy Systems Analysis

Sr. Financial Analyst, Sponsored Products and Brands Finance

Senior Quantitative Risk Analyst

Common Questions