{ "count" : 20589, "data" : [ { "id" : "6a2c6a4874d8ee00a090b1a3", "title" : "Quantitative Researcher - Prediction Markets, Quant Trading", "industry" : "Quant Middle Office", "salary" : { "min" : 100000.0, "max" : 150000.0, "currency" : "USD", "frequency" : "yearly" }, "location" : "Dallas, Texas", "locations" : [ "Dallas, Texas" ], "timestamp" : "2026-06-15T23:14:56.613", "fingerprint" : "9569170f5017b55fc157e3b97703dde0c5cf3ee4a0aad9fb3706930eddb5a7c9", "source" : "lever", "language" : "en", "applyUrl" : "https://jobs.lever.co/crypto/5e8ddb0f-c326-41d3-be2e-382be2b5a3e0/apply", "externalId" : "5e8ddb0f-c326-41d3-be2e-382be2b5a3e0", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Dallas", "state" : "Texas", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "32.7762719,-96.7968559" } ], "locationText" : "Dallas, Texas, United States", "employmentType" : "FULL_TIME", "technicalSkills" : "Python", "professionalSkills" : [ "Pricing models", "Market making", "Risk models", "Data engineering", "Backtesting", "Simulation", "Model validation" ], "hardSkillsList" : [ "Quantitative analysis", "Data modeling", "Statistical modeling", "Machine learning" ], "hardSkills" : [ { "name" : "Quantitative analysis", "level" : "intermediate" }, { "name" : "Data modeling", "level" : "intermediate" }, { "name" : "Statistical modeling", "level" : "intermediate" }, { "name" : "Machine learning", "level" : "intermediate" } ], "majorSkills" : "Quantitative research, Prediction markets, Quant trading, Data pipelines", "majorSkillsList" : [ "Quantitative research", "Prediction markets", "Quant trading", "Data pipelines" ], "coreResponsibilities" : "Build data foundation, Transform raw data into pricing inputs, Research quantitative pricing models, Develop quantitative pricing models, Research market-making models, Develop market-making models, Research risk models, Develop risk models, Model cross-market dependencies, Model correlations, Model portfolio effects, Build frameworks for backtesting, Build frameworks for simulation, Build frameworks for model validation, Create tools to monitor model performance, Create tools to monitor calibration, Create tools to monitor P&L attribution, Create tools to monitor live trading outcomes, Define tooling for new team, Define workflow for new team, Define research standards for new team", "teamCollaboration" : "Close collaboration with traders", "domainKnowledge" : "Prediction markets; Player props; Parlays; Combinatorial products; Sports markets; Non-sports markets; Contract types", "domainList" : [ "prediction-markets", "player-props", "parlays", "combinatorial-products", "sports-markets", "non-sports-markets", "contract-types" ], "domainSpecificKnowledge" : [ "Prediction markets", "Player props", "Parlays", "Combinatorial products", "Sports markets", "Non-sports markets", "Contract types" ], "qualificationsBasic" : "Quantitative background in statistics, math, ML, economics, Experience building models in trading, sports, betting, prediction markets, Python/data skills, Comfort owning data pipelines, Comfort owning modeling, Ability to move quickly from raw data to research insight to production-ready mode, High ownership, Communication skills, Comfortable with fast-paced high growth environment", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "## Description We’re building a new quantitative research team focused on pricing, market-making, and risk models for prediction markets. This is a highly hands-on role for someone who can operate end-to-end: data engineering, research, modeling, and close collaboration with traders, across sports and non-sports event markets and a range of contract types, including single-outcome markets, player props, and parlays. ## Responsibilities Build data foundation, transform raw data into pricing inputs Research and develop quantitative pricing, market-making, and risk models across sports, non-sports, player props, parlays, and correlated markets Model cross-market dependencies, correlations, and portfolio effects, especially for combinatorial products such as parlays Partner closely with traders to improve pricing logic, market coverage, and trading performance Build frameworks for backtesting, simulation, and model validation Create tools to monitor model performance, calibration, P&L attribution, and live trading outcomes Help define the tooling, workflow, and research standards for a new team ## Requirements Strong quantitative background in statistics, math, ML, economics, or a related field Experience building models in trading, sports, betting, prediction markets, or similar domains Strong Python/data skills and comfort owning data pipelines as well as modeling Ability to move quickly from raw data to research insight to production-ready mode High ownership, strong communication skills and comfortable with fast-paced high growth environment", "summaryDescription" : "Quantitative Researcher - Prediction Markets, Quant Trading. 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Transform raw data into pricing inputs", "postedDate" : "2026-06-12T01:56:10.179", "createdAt" : "2026-06-12T01:56:10.179", "lastUpdated" : "2026-06-15T23:14:56.613", "ingestTimestamp" : "2026-06-14T22:03:02.708", "mongoId" : "6a2c6a4874d8ee00a090b1a3", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 100000, "salaryAnnualMax" : 150000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Quantitative analysis", "Data modeling", "Statistical modeling", "Machine learning", "Quantitative research", "Prediction markets", "Quant trading", "Data pipelines", "Pricing models", "Market making", "Risk models", "Data engineering", "Backtesting", "Simulation", "Model validation", "Player props", "Parlays", "Combinatorial products", "Sports markets", "Non-sports markets", "Contract types" ], "skillCount" : 21, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Mid", "dataQualityScore" : 0.7777778, "_score" : 2805.1394, "daysOld" : 3, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c938274d8ee00a0988438", "title" : "Quant Trade Researcher", "company" : "AlgoQuant Asset Management", "industry" : "FinTech", "salary" : { "min" : 140000.0, "max" : 210000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for FinTech in Bulgaria, adjusted for Lead seniority and remote work." }, "location" : "Remote", "locations" : [ "Remote" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T04:53:35.849", "fingerprint" : "2192ba4d9f25504ffbe0daee21512825062737a64fc63dce49452d5758bb5171", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/algoquant/jobs/4873030101", "externalId" : "4873030101", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Bulgaria", "continent" : "eu", "workMode" : "remote" } ], "locationText" : "Bulgaria", "technicalSkills" : "Python, C++, Rust, SQL", "professionalSkills" : [ "Quantitative analysis", "Systematic trading", "Statistical validation" ], "hardSkillsList" : [ "Statistical modeling", "Machine learning", "Data quality analysis", "Bias detection" ], "softSkillsList" : [ "High agency", "Relentless curiosity" ], "hardSkills" : [ { "name" : "Statistical modeling", "level" : "intermediate" }, { "name" : "Machine learning", "level" : "intermediate" }, { "name" : "Data quality analysis", "level" : "intermediate" }, { "name" : "Bias detection", "level" : "intermediate" } ], "softSkills" : [ { "name" : "High agency" }, { "name" : "Relentless curiosity" } ], "majorSkills" : "Quantitative trading, Machine learning, Data analysis", "majorSkillsList" : [ "Quantitative trading", "Machine learning", "Data analysis" ], "coreResponsibilities" : "Design systematic trading strategies, Test systematic trading strategies, Deploy systematic trading strategies, Generate trading ideas, Validate trading ideas, Ship signals into live capital, Own research end-to-end", "teamCollaboration" : "Work with portfolio managers; Work with engineers", "domainKnowledge" : "Digital asset markets; Systematic trading; Boosting algorithms; Transformers; Reinforcement learning; Crypto exposure", "domainList" : [ "digital-asset-markets", "systematic-trading", "boosting-algorithms", "transformers", "reinforcement-learning", "crypto-exposure" ], "domainSpecificKnowledge" : [ "Digital asset markets", "Systematic trading", "Boosting algorithms", "Transformers", "Reinforcement learning", "Crypto exposure" ], "problemSolvingSkills" : "Relentlessly analytical; Unsolved problem analysis", "outcomesObjectives" : "Ship signals in weeks", "qualificationsBasic" : "5+ years experience, Python required, SQL proficiency, Minimum 5 years experience", "qualificationsPreferred" : "Junior candidates research track record, Senior candidates live track record, PhD preferred, GCP Professional Data Engineer, AWS Data Analytics, Databricks Certified, Dbt Certified", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Quant Trade Researcher AlgoQuant Asset Management Dubai (preferred) · London · New York – Reports to Head of Research – Rolling start About AlgoQuant AlgoQuant Asset Management is a multi-strategy digital asset manager allocating capital across 25+ internal and external quantitative trading pods. Founded in 2018, we have evolved into an institutional platform combining trading edge with strong governance and advanced technology, serving family offices and institutional investors globally. The role We are hiring Quant Trade Researchers at both junior and senior levels to design, test, and deploy systematic trading strategies across digital asset markets. You will generate ideas from first principles, validate them with rigorous statistics, and ship signals into live capital, in weeks, not quarters. You will work directly with portfolio managers and engineers who move at your pace. This role is for people who live in data, mathematics, and code, relentlessly analytical, hungry for P strong experience implementing a wide range of models, including boosting algorithms, transformers, and reinforcement learning. 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United States", "employmentType" : "FULL_TIME", "technicalSkills" : "Python, C++, Rust, SQL, Machine Learning", "professionalSkills" : [ "Quantitative research", "Quantitative analysis", "Development", "Market microstructure analysis", "Statistical analysis", "Machine-learning techniques", "Trading signal generation", "Trading signal validation", "Trading signal improvement", "Market-making strategies", "Arbitrage strategies", "Systematic strategies", "Signal-generation pipelines", "Feature stores", "Parameter-optimization tooling", "Backtesting", "Performance analysis", "Performance attribution", "Trading system components", "Order management", "Exchange connectivity", "Data pipelines", "Research platforms", "System reliability", "Scalability", "Latency optimization", "Performance optimization", "Risk monitoring", "Risk control systems", "Post-trade analytics", "Execution quality evaluation", "Slippage evaluation", "Market impact evaluation", "Risk metrics development", "Dashboards", "Reporting tools", "Strategy oversight", "Portfolio oversight", "Simulations", "Market impact estimation", "Probability", "Statistics", "Time-series modeling", "Quantitative methods", "Data structures", "Algorithms", "Software engineering", "Version control", "Financial markets", "Trading concepts", "Risk-management principles" ], "hardSkillsList" : [ "Statistical analysis", "Machine-learning techniques", "Time-series modeling", "Quantitative methods", "Data structures", "Algorithms", "Software engineering", "Version control", "Backtesting methodologies", "Strategy development", "Risk monitoring", "Risk control", "Execution quality", "Market impact", "Risk metrics", "HFT development" ], "hardSkills" : [ { "name" : "Statistical analysis", "level" : "intermediate" }, { "name" : "Machine-learning techniques", "level" : "intermediate" }, { "name" : "Time-series modeling", "level" : "intermediate" }, { "name" : "Quantitative methods", "level" : "intermediate" }, { "name" : "Data structures", "level" : "intermediate" }, { "name" : "Algorithms", "level" : "intermediate" }, { "name" : "Software engineering", "level" : "intermediate" }, { "name" : "Version control", "level" : "intermediate" }, { "name" : "Backtesting methodologies", "level" : "intermediate" }, { "name" : "Strategy development", "level" : "intermediate" }, { "name" : "Risk monitoring", "level" : "intermediate" }, { "name" : "Risk control", "level" : "intermediate" }, { "name" : "Execution quality", "level" : "intermediate" }, { "name" : "Market impact", "level" : "intermediate" }, { "name" : "Risk metrics", "level" : "intermediate" }, { "name" : "HFT development", "level" : "intermediate" } ], "majorSkills" : "Quantitative research, Automated trading, Low-latency execution, Real-time market data", "majorSkillsList" : [ "Quantitative research", "Automated trading", "Low-latency execution", "Real-time market data" ], "coreResponsibilities" : "Analyze market microstructure, Analyze on-chain data, Identify inefficiencies, Identify trading opportunities, Apply statistical techniques, Apply machine-learning techniques, Generate trading signals, Validate trading signals, Improve trading signals, Design market-making strategies, Design arbitrage strategies, Design systematic strategies, Implement market-making strategies, Implement arbitrage strategies, Implement systematic strategies, Build signal-generation pipelines, Build feature stores, Build parameter-optimization tooling, Maintain signal-generation pipelines, Maintain feature stores, Maintain parameter-optimization tooling, Develop robust backtesting, Conduct performance analysis, Conduct attribution, Implement trading system components, Implement order management, Implement exchange connectivity, Build data pipelines, Build research platforms, Operate data pipelines, Operate research platforms, Ensure system reliability, Ensure scalability, Ensure latency optimization, Ensure performance optimization, Implement risk monitoring systems, Implement risk control systems, Run post-trade analytics, Evaluate execution quality, Evaluate slippage, Evaluate market impact, Develop risk metrics, Develop dashboards, Develop reporting tools, Run simulations, Estimate market impact", "teamCollaboration" : "Quantitative team", "domainKnowledge" : "Financial markets; Trading concepts; Risk-management principles; Cryptocurrency markets; DeFi protocols; On-chain analytics; Blockchain technology; Smart-contract fundamentals; MEV-aware strategies", "domainList" : [ "financial-markets", "trading-concepts", "risk-management-principles", "cryptocurrency-markets", "defi-protocols", "on-chain-analytics", "blockchain-technology", "smart-contract-fundamentals", "mev-aware-strategies" ], "domainSpecificKnowledge" : [ "Financial markets", "Trading concepts", "Risk-management principles", "Cryptocurrency markets", "DeFi protocols", "On-chain analytics", "Blockchain technology", "Smart-contract fundamentals", "MEV-aware strategies" ], "toolProficiency" : [ "Python", "C++", "Rust", "Linux", "DevOps" ], "problemSolvingSkills" : "Data/logic error resolution", "qualificationsBasic" : "M. S. or Ph. D, 3–5 years experience, HFT development experience, Expert-level Python, Solid grasp of data structures, Solid grasp of algorithms, Solid grasp of software engineering, Solid grasp of version control, Experience with statistical analysis, Experience with backtesting, Experience with strategy development, Ability to create algorithms, Understanding of financial markets, Understanding of trading concepts, Understanding of risk-management principles", "qualificationsPreferred" : "Experience with machine-learning frameworks, Experience with distributed computing, Experience with parallel computing, Familiarity with Linux development, Familiarity with modern DevOps, Understanding of cryptocurrency markets, Understanding of DeFi protocols, Understanding of on-chain analytics, Experience with real-time trading systems, Experience with low-latency applications, Experience with exchange integrations, Knowledge of blockchain technology, Knowledge of smart-contract fundamentals, Knowledge of MEV-aware strategies, Professional certifications, Prior experience in quantitative trading, Prior experience in fintech, Publications in relevant fields", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "ABOUT INJECTIVE LABS Injective Labs is trailblazing a new dawn for Web3 enabled finance. We are the core contributors to Injective, one of the fastest growing blockchains in the industry. Injective provides an interoperable smart contracts platform that is optimized for building decentralized finance applications. Interoperability is at the core of Injective, which is natively integrated with chains such as Ethereum, Cosmos and Solana. Developers can rapidly launch premier financial applications suited for mass adoption using Injective’s infrastructure and specialized DeFi primitives such as the world’s first fully on-chain order book. Our team has decades of experience spearheading the largest financial institutions and tech organizations. Injective is incubated by Binance and is backed by leading firms such as Jump Crypto, Pantera and Mark Cuban. ABOUT THE ROLE We are looking for a Quantitative Researcher to fit into our existing highly-skilled NY-based quantitative team. As a part of our Quant team you’ll be studying the crypto market to find profitable trading opportunities and build automated trading strategies. The ideal candidate would be someone who has experience working with low-latency execution engines, handling real-time market data, and producing strategies that react immediately to market changes. If this sounds like you and you enjoy working in fast paced environments, this role is for you! RESPONSIBILITIES: - Analyze market microstructure and on-chain data to identify inefficiencies and trading opportunities. - Apply statistical and machine-learning techniques to generate, validate, and improve trading signals. - Design and implement market-making, arbitrage, and systematic strategies end-to-end. - Build and maintain signal-generation pipelines, feature stores, and parameter-optimization tooling. - Develop robust backtesting frameworks; conduct performance analysis and attribution. - Implement trading system components, including order management and exchange connectivity. - Build and operate data pipelines and research platforms for high-quality, reproducible research. - Ensure system reliability, scalability, and latency/performance optimization in production. - Implement risk monitoring and control systems across strategies and venues. - Run post-trade analytics to evaluate execution quality, slippage, and market impact. - Develop risk metrics, dashboards, and reporting tools for strategy and portfolio oversight. - Run simulations and estimate market impact for both liquid and illiquid assets. WHO YOU ARE: - M.S. or Ph.D. in Mathematics, Physics, Statistics, Computer Science, or a related quantitative field. - 3–5 years of quantitative research/analysis or development experience. - Experience in HFT development. - Strong foundation in probability, statistics, time-series modeling, and quantitative methods. - Expert-level Python for research and production; proficiency in C++ or Rust for performance-critical components. - Solid grasp of data structures, algorithms, software engineering principles, and version control. - Experience with statistical analysis, backtesting methodologies, and strategy development. - Ability to create and use algorithms to investigate large datasets and resolve data/logic errors with rigor. - Understanding of financial markets, trading concepts, and risk-management principles. PREFERRED: - Experience with machine-learning frameworks and distributed/parallel computing. - Familiarity with Linux development environments and modern DevOps practices. - Understanding of cryptocurrency markets, DeFi protocols, and on-chain analytics. - Experience with real-time trading systems, low-latency applications, and exchange integrations. - Knowledge of blockchain technology, smart-contract fundamentals, and MEV-aware strategies. - Professional certifications (e.g., CFA, FRM), prior experience in quantitative trading/fintech, and/or publications in relevant fields. WHY WORK WITH US? - Competitive salary and INJ token award. - Unlimited PTO. - Health Insurance. - Equipment. - Home Office Stipend. - Flexible working hours. - Opportunity to work on cutting-edge blockchain technology in the finance industry. - Collaborative team culture with opportunities for professional growth and development. - Global team meet ups. HOW TO APPLY To apply for this position, please submit your application through the following link: https://injectivelabs.org/careers?ashby_jid=9e4d708a-b599-4d26-97f5-a66ab5c6ea64#open-roles Only applications submitted through this link will be considered. As an equal opportunity employer we don’t tolerate discrimination or harassment of any kind. Whether that’s based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status or any other protected characteristic as outlined by federal, state or local laws. We will only contact candidates using emails from the @injective.foundation http://injective.foundation domain. If you are approached by any other account or domain regarding this position, it was not sent by us. Please stay cautious and report any suspicious communication.", "summaryDescription" : "Quant Researcher at Injective Labs. 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We specialize in providing liquidity as an options market-maker – meaning we are committed to providing competitive quotes that we are willing to both buy and sell. To do this successfully, we design and implement our own low latency technologies, trading strategies and mathematical models. Our Founding Partners first conceptualized Akuna in their hometown of Sydney. They opened the firm’s first office in 2011 in the heart of the derivatives industry and the options capital of the world – Chicago. Today, Akuna is proud to operate from additional offices in Sydney, Shanghai, London, and Singapore. What you’ll do as a Virtual Quant Trading Challenge Participant: Are you quantitative, competitive, proficient with Python and looking to test your skills in a Quantitative Trading environment? Break into the Trading industry by participating in our latest simulation! Candidates will gain hands-on trading experience by writing their own market-making bots which will compete both against our models and one another on a simulated exchange. The most profitable submissions will win Akuna swag and expedited recruitment processes in our Quant full-time and internship roles in Chicago! The challenge will take about 5-8 hours to complete, and the competition will be open for 1 week (from August 17th – August 21st). Qualities that make great candidates: Able to dedicate 5-8 hours uninterrupted to complete the challenge from August 17th through August 21st 2026. Pursuing a BS/MS/ PhD in Engineering, Economics, Statistics, Mathematics, Computer Science, Actuarial Science or a related/equivalent field. Strong math aptitude, statistical and quantitative analysis skills. Strong Python programming background. Entrepreneurial self-starter ready to work in a fast paced, competitive, team environment. Desire and ability to learn the intricacies of financial markets. Major GPA of 3.5 or above Graduating between December 2026 – August 2028. In addition to technical skillsets, Akuna values the unique perspectives people can bring to the table to collaboratively solve complex problems and drive Akuna forward. We want all candidates to feel empowered to apply, even if you don’t meet every qualification. We welcome your application and encourage you to take the first steps toward your future with us! Application Process: Applications open on 6/11/2026 and close on 8/10/2026. Submit your resume and a one-page/500 words max motivation letter describing your interest in Akuna Capital and detailing what sets you apart from other applicants. A limited number of candidates will be invited to join the Quant Trading challenge. Individual submissions only – no teams. Top performers will have the opportunity to be expedited to final round interviews for our roles within our Quant department at the end of the program. Any offer of employment from Akuna is ultimately contingent on verification of your right to work in the United States on the first day of employment, consent to a background check including the successful review and completion of such background check, and review and execution of the Company's Restrictive Covenant and Employee Work Made for Hire Agreement. **Resumes and motivations letters must be submitted in PDF format.", "summaryDescription" : "Virtual Quant Trading Challenge at Akuna Capital. Skills: Quantitative trading, Market making bots. Write market-making bots. Compete on simulated exchange", "postedDate" : "2026-06-14T02:39:55.655", "createdAt" : "2026-06-14T02:39:55.655", "lastUpdated" : "2026-06-15T04:47:40.510", "ingestTimestamp" : "2026-06-14T02:39:55.655", "mongoId" : "6a2ca36774d8ee00a09ab9c3", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 60000, "salaryAnnualMax" : 80000, "salaryBand" : "50k-75k", "hasSalary" : true, "allSkills" : [ "Statistical analysis", "Quantitative analysis", "Quantitative trading", "Market making bots", "Market making", "Financial markets" ], "skillCount" : 6, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 1484.6967, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c938274d8ee00a0988439", "title" : "Senior Quant Researcher", "company" : "AlgoQuant", "industry" : "FinTech", "salary" : { "min" : 4500000.0, "max" : 7500000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Quant Researcher in FinTech, adjusted for seniority and remote work in India." }, "location" : "Remote", "locations" : [ "Remote" ], "timestamp" : "2026-06-15T07:13:46.496", "fingerprint" : "d87dc070a942e649fb7a20fa462379498259408836ec40e2cfc06ce00f1a2bda", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/algoquant/jobs/4876669101", "externalId" : "4876669101", "industryFunction" : { }, "structuredLocations" : [ { "workMode" : "remote" } ], "locationText" : "", "minimumEducation" : "PhD", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, R, Scala, Spark, SQL, Transformers, Graph neural networks, Reinforcement learning, XGBoost, LightGBM, MLflow, AWS, GCP, Azure, SageMaker, Vertex AI, ML Studio, Delta Lake", "professionalSkills" : [ "Quantitative analysis", "Alpha generation", "Strategy development", "Signal generation", "Data architecture", "Performance attribution", "Methodology development" ], "hardSkillsList" : [ "Machine learning", "Deep learning", "Feature engineering", "Model validation", "Statistical rigour", "Non-linear signal generation", "Financial prediction", "Lookahead bias prevention", "Data leakage prevention", "Overfitting prevention", "Microstructure analysis", "Order flow analysis", "Cross-venue dynamics" ], "softSkillsList" : [ "Self-directed", "High-agency", "Intellectual curiosity" ], "hardSkills" : [ { "name" : "Machine learning", "level" : "intermediate" }, { "name" : "Deep learning", "level" : "intermediate" }, { "name" : "Feature engineering", "level" : "intermediate" }, { "name" : "Model validation", "level" : "intermediate" }, { "name" : "Statistical rigour", "level" : "intermediate" }, { "name" : "Non-linear signal generation", "level" : "intermediate" }, { "name" : "Financial prediction", "level" : "intermediate" }, { "name" : "Lookahead bias prevention", "level" : "intermediate" }, { "name" : "Data leakage prevention", "level" : "intermediate" }, { "name" : "Overfitting prevention", "level" : "intermediate" }, { "name" : "Microstructure analysis", "level" : "intermediate" }, { "name" : "Order flow analysis", "level" : "intermediate" }, { "name" : "Cross-venue dynamics", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Self-directed" }, { "name" : "High-agency" }, { "name" : "Intellectual curiosity" } ], "majorSkills" : "Machine learning, Deep learning, Alpha generation, Quantitative research", "majorSkillsList" : [ "Machine learning", "Deep learning", "Alpha generation", "Quantitative research" ], "coreResponsibilities" : "Design ML models, Deploy ML models, Generate alpha signals, Engineer features, Select architectures, Validate models, Monitor live signals, Adapt techniques, Build research pipelines, Prevent lookahead bias, Prevent data leakage, Prevent overfitting, Analyse microstructure, Analyse order flow, Analyse cross-venue dynamics, Enrich feature sets, Improve signal quality, Collaborate with engineers, Move models to production, Mentor junior researchers, Raise statistical rigour, Contribute to infrastructure, Contribute to tooling, Contribute to datasets", "teamCollaboration" : "With engineers; With research team", "projectManagementSkills" : [ "End-to-end research ownership" ], "domainKnowledge" : "Digital asset markets; On-chain data; Spot markets; Derivatives markets; Transformer architectures; Graph neural networks; Reinforcement learning; Ensemble methods; Financial prediction; Market structure", "domainList" : [ "digital-asset-markets", "on-chain-data", "spot-markets", "derivatives-markets", "transformer-architectures", "graph-neural-networks", "reinforcement-learning", "ensemble-methods", "financial-prediction", "market-structure" ], "domainSpecificKnowledge" : [ "Digital asset markets", "On-chain data", "Spot markets", "Derivatives markets", "Transformer architectures", "Graph neural networks", "Reinforcement learning", "Ensemble methods", "Financial prediction", "Market structure" ], "toolProficiency" : [ "ML frameworks", "Hugging Face" ], "innovationCreativity" : "Next generation alpha research", "problemSolvingSkills" : "Complex non-linear signal generation", "outcomesObjectives" : "Turn predictive signal into strategy", "qualificationsBasic" : "PhD or equivalent research depth, Machine learning expertise, Deep learning expertise, Hands-on implementation experience, Live, capital-at-risk environment experience, SQL proficiency, 5+ years Python experience", "qualificationsPreferred" : "PhD preferred, Experience with unconventional on-chain data, C++ or Rust a plus, Cloud platform certs", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Senior Quant Researcher AlgoQuant Asset Management Dubai (preferred) · London · New York – Reports to Head of Research – Rolling start About AlgoQuant AlgoQuant Asset Management is a multi-strategy digital asset manager allocating capital across 25+ internal and external quantitative trading pods. Founded in 2018, we have evolved into an institutional platform combining trading edge with strong governance and advanced technology, serving family offices and institutional investors globally. The role We are hiring a Senior Quant Researcher with deep machine learning and deep learning expertise to drive the next generation of alpha research at AlgoQuant. This is a senior, high-ownership role for someone who has moved beyond applying ML frameworks — you understand why models work, where they break, and how to turn raw predictive signal into live, capital-weighted strategy. You will lead research into complex, non-linear signal generation across digital asset markets, working across spot, derivatives, and on-chain data. You will own research end-to-end: from problem formulation and data architecture through to live deployment and performance attribution. You will also set the standard for rigour and methodology across the research team. Responsibilities ● Design and deploy advanced ML and DL models for alpha signal generation across digital asset markets ● Work across the full model stack: feature engineering, architecture selection, training and validation regimes, and live signal monitoring ● Apply and adapt state-of-the-art techniques — transformer architectures, graph neural networks, reinforcement learning, and ensemble methods — to financial prediction problems ● Build robust, production-grade research pipelines with a rigorous approach to preventing lookahead bias, data leakage, and overfitting ● Analyse microstructure, order flow, and cross-venue dynamics to enrich feature sets and improve signal quality ● Collaborate with engineers to move models from research to production infrastructure ● Mentor junior researchers and raise the bar for statistical rigour across the team ● Contribute to shared research infrastructure, tooling, and datasets What we are looking for ● Exceptional quantitative background — PhD or equivalent research depth in machine learning, statistics, physics, mathematics, or computer science ● Genuine expertise in modern ML and DL: transformers, attention mechanisms, graph neural networks, boosting algorithms (XGBoost, LightGBM), and reinforcement learning — not just familiarity, but hands-on implementation experience ● A track record of applying ML in a live, capital-at-risk environment — attributable P C++ or Rust a strong plus for production performance ● Experience working with large, complex, or unconventional datasets; on-chain data experience a plus ● Self-directed and high-agency — you set your own research agenda and drive it to completion ● Crypto market exposure a strong plus; intellectual curiosity about digital asset market structure essential", "summaryDescription" : "Senior Quant Researcher at AlgoQuant. Skills: Machine learning, Deep learning, Alpha generation, Quantitative research. Design ML models. Deploy ML models", "postedDate" : "2026-06-13T22:37:16.533", "createdAt" : "2026-06-13T22:37:16.533", "lastUpdated" : "2026-06-15T07:13:46.496", "ingestTimestamp" : "2026-06-13T22:37:16.533", "mongoId" : "6a2c938274d8ee00a0988439", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Machine learning", "Deep learning", "Feature engineering", "Model validation", "Statistical rigour", "Non-linear signal generation", "Financial prediction", "Lookahead bias prevention", "Data leakage prevention", "Overfitting prevention", "Microstructure analysis", "Order flow analysis", "Cross-venue dynamics", "Self-directed", "High-agency", "Intellectual curiosity", "Alpha generation", "Quantitative research", "Quantitative analysis", "Strategy development", "Signal generation", "Data architecture", "Performance attribution", "Methodology development", "End-to-end research ownership", "Digital asset markets", "On-chain data", "Spot markets", "Derivatives markets", "Transformer architectures", "Graph neural networks", "Reinforcement learning", "Ensemble methods", "Market structure", "ML frameworks", "Hugging Face" ], "skillCount" : 36, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "_score" : 1435.5782, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.98 }, { "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" : 1430.5115, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "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" : 1413.1531, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.98 }, { "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. 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Global matrix teams", "domainKnowledge" : "Sports domain; Prediction markets; Real-time sports data; Distributed state machines", "domainList" : [ "sports-domain", "prediction-markets", "real-time-sports-data", "distributed-state-machines" ], "domainSpecificKnowledge" : [ "Sports domain", "Prediction markets", "Real-time sports data", "Distributed state machines" ], "continuousLearning" : "Develop new skill-sets; Internal mobility program", "innovationCreativity" : "Find innovative solutions", "problemSolvingSkills" : "Identify bottlenecks; Diagnose bottlenecks; Resolve bottlenecks", "qualificationsBasic" : "Mid-to-senior level backend experience, Golang production-level mastery, Experience with Sports systems, Experience with Sportsbooks, Experience with Prediction markets, Experience with high-velocity sports-data infrastructure, Proficiency in Golang, Proficiency in Postgres, Proficiency in Redis, Proficiency in Kafka, Elite interpersonal skills, Capacity for stakeholder management, Navigate cross-functional teams, Manage competing project priorities", "qualificationsPreferred" : "Familiarity with transaction-heavy modules, Familiarity with money-related modules, Familiarity with payment ledgers, Advanced expertise in concurrent systems, Advanced expertise in race-condition mitigation, Advanced expertise in distributed state machines, Experience in rapid startup environment, Experience in ambiguous startup environment, Experience in entrepreneurial startup environment", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "## RESPONSIBILITIES Design, develop, and optimize robust, highly scalable backend services and distributed systems in Golang to power our 24/7 global trading and sports-domain applications. Develop backend services and operations, including proposing architectural decisions, participating in design reviews, coding, code review, and implementing features Act as the technical subject matter expert to increase and embed deep sports domain knowledge into our core backend, building features tailored to prediction markets, real-time sports data feeds, and interactive mechanics. Identify, diagnose, and resolve architectural bottlenecks within a large-scale, high-concurrency infrastructure Operational Support: Provide high-tier technical operational support to address complex, real-time client issues and maintain flawless systemic availability. ## REQUIREMENTS Minimum Qualifications (Must-Haves): Solid mid-to-senior level professional experience specializing in backend system development, with an absolute proficiency and production-level mastery. Proven experience working closely with Sports systems, Sportsbooks, Prediction markets, or high-velocity sports-data infrastructure. Proficiency in Golang, Postgres, Redis, and Kafka preferred Communication & Collaboration: Elite interpersonal skills with a strong capacity for stakeholder management; comfortable navigating cross-functional, global matrix teams and managing competing project priorities. Preferred Qualifications (Nice-to-Haves / Ideal Fits): Deep familiarity with transaction-heavy, money-related modules, or payment ledgers. Advanced expertise in designing complex concurrent systems, race-condition mitigation, and distributed state machines. Previous professional experience operating smoothly within a rapid, ambiguous, or highly entrepreneurial startup environment. ## Additional Information Life @ Crypto.com Empowered to think big. Try new opportunities while working with a talented, ambitious and supportive team. Transformational and proactive working environment. Empower employees to find thoughtful and innovative solutions. Growth from within. We help to develop new skill-sets that would impact the shaping of your personal and professional growth. Work Culture. Our colleagues are some of the best in the industry; we are all here to help and support one another. One cohesive team. Engage stakeholders to achieve our ultimate goal - Cryptocurrency in every wallet. Work Flexibility Adoption. Flexi-work hour and hybrid or remote set-up Aspire career alternatives through us - our internal mobility program offers employees a new scope. Are you ready to kickstart your future with us? Benefits Competitive salary Attractive annual leave entitlement including: birthday, work anniversary 401(k) plan with employer match Eligible for company-sponsored group health, dental, vision, and life/disability insurance Work Flexibility Adoption. Flexi-work hour and hybrid or remote set-up Aspire career alternatives through us. Our internal mobility program can offer employees a diverse scope. Our Crypto.com benefits packages vary depending on region requirements, you can learn more from our talent acquisition team. About Crypto.com: Founded in 2016, Crypto.com serves more than 150 million customers and is the world's fastest growing global cryptocurrency platform. Our vision is simple: Cryptocurrency in Every Wallet™. Built on a foundation of security, privacy, and compliance, Crypto.com is committed to accelerating the adoption of cryptocurrency through innovation and empowering the next generation of builders, creators, and entrepreneurs to develop a fairer and more equitable digital ecosystem. Learn more at https://crypto.com. Crypto.com is an equal opportunities employer and we are committed to creating an environment where opportunities are presented to everyone in a fair and transparent way. Crypto.com values diversity and inclusion, seeking candidates with a variety of backgrounds, perspectives, and skills that complement and strengthen our team. Personal data provided by applicants will be used for recruitment purposes only. Please note that only shortlisted candidates will be contacted.", "summaryDescription" : "Senior Backend Engineer (Sports & Prediction Markets) – Golang at Crypto.com. Skills: Backend services, Distributed systems, Golang, Prediction markets. Design backend services. 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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. 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Explain P&L attribution", "innovationCreativity" : "R&D projects", "problemSolvingSkills" : "Root cause analysis", "qualificationsBasic" : "Hands-on experience quantitative energy trading, BESS optimisation experience, Algorithmic trading European power markets, Expertise optimisation methods, Solid Python skills, Familiarity European market infrastructure, Track record leading quant team, Fluent English", "qualificationsPreferred" : "Experience with SDDP, Experience multiple European market zones, Knowledge of REMIT/REMIT-II compliance, Experience with ETRM systems, Experience building proprietary trading infrastructure, German is a plus", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "Why The Mobility House? Help shape our vision of an emission-free energy and mobility future High levelof responsibility and rapid development in a growing and innovative company Open, diverse & international team Flexible working hours and additiona lvacation days Mobile working from home and 20 days in other European countries Choice between the latest Apple and Dell IT equipment Subsidy for Deutschlandticket job Wellpass membership Lease of your preferred car and bike via FINN or JobRad Modern office with good public transport connections A greenfield mandate: you’ll shape the algorithmic architecture of a growing multi-market BESS and EV flexibility trading business Direct collaboration with the Head of Trading, Trading Leads, and platform engineering - short decision paths, high ownership A live portfolio spanning ~600 MW across five European countries, with active expansion into Southeast Europe Competitive compensation with performance component What you do Our trading & optimization is scaling fast. We currently optimise and market a ~600 MW portfolio of battery storage systems and aggregated EV flexibility across Day-Ahead, Intraday and reserve markets in five European countries - and we’re just getting started. We’re looking for someone who builds the algorithmic engine on top of our trading platform - not just maintaining what exists, but designing the optimisation framework that will drive our next phase of growth. You’ll lead a small, high-calibre team of quant traders, analyst and data scientists, work closely with the Head of Trading and Trading Analytics and Tech, and own the full lifecycle from research to production. This role is for someone who is equally at home writing a stochastic dispatch optimiser, reviewing a backtest, or explaining model assumptions to a senior stakeholder. Designing and owning the algorithmic optimisation stack - multi-market dispatch optimisation, stochastic bidding strategies across DA, ID, FCR, aFRR and mFRR, and real-time decision logic for BESS assets Leading a team of 7 Quant Traders, Analyst and Data Scientists - setting direction, prioritising the roadmap, running code reviews, and building a strong delivery culture Driving the research-to-production pipeline: from hypothesis and backtesting through validation, deployment with Tech, and continuous performance monitoring Advancing the automation agenda together with the Platform teams. Building and maintaining BESS valuation and degradation models at fleet scale, incorporating physical constraints, cycle costs, and multi-market opportunity costs Acting as the key technical interface between quant models and trading strategy - translating trader intuition or quant insights into formal optimisation problems and communicating model outputs clearly Serving as key sparring partner for the senior leadership on algorithm performance, market structure changes, and quantitative strategy Who you are Several years of hands-on experience in quantitative energy trading, BESS optimisation, or algorithmic trading in European power markets - you understand both the math and the commercial logic Deep expertise in optimisation methods: LP/MIP, stochastic dynamic programming, rolling intrinsic or SDDP approaches for storage dispatch Solid Python skills and strong quantitative mindset – including financial modelling, risk assessment and data-driven decision making Familiarity with European market infrastructure (EPEX SPOT, XBID, TSO reserve market platforms) and data APIs Track record of leading or mentoring a quant or dev team - you create clarity, enable autonomy, and hold a high technical bar without micromanaging Strong communicator: you can explain a stochastic optimisation model to a trader and a P&L attribution to senior management Fluent English, German is a plus Nice to have: Experience with SDDP (Stochastic Dual Dynamic Programming) or similar scenario-tree approaches for multi-period storage valuation Background in Monte Carlo simulation for extrinsic value modelling or DA-SWAP pricing on BESS assets Exposure to multiple European market zones (DE/AT, FR, BE, SE, BG or similar) Knowledge of REMIT / REMIT-II compliance requirements Experience with ETRM systems or building proprietary trading infrastructure Are you a good fit for us? Diversity enriches our team and makes us stronger. Regardless of origin, gender, age, sexual orientation, religion, or any disability – everyone is welcome here! We look forward to receiving your application and achieving great things together. Your contact person Vanessacareer@mobilityhouse.com", "summaryDescription" : "Team Lead (m/f/d) Quant Trading at The Mobility House. Skills: Algorithmic optimisation, Stochastic bidding, BESS valuation, Quant trading. Design optimisation framework. 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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. 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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. 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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. 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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" : 1155.0907, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "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" : 1146.3878, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "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. 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Quant Researchers collaboration", "projectManagementSkills" : [ "Agile development" ], "domainKnowledge" : "Financial markets; Asset pricing theory; Equity market neutral models", "domainList" : [ "financial-markets", "asset-pricing-theory", "equity-market-neutral-models" ], "domainSpecificKnowledge" : [ "Financial markets", "Asset pricing theory", "Equity market neutral models" ], "toolProficiency" : [ "Airflow", "Kafka", "Bitbucket", "Jenkins", "Grafana", "Prometheus", "ELK", "Docker", "Kubernetes", "OpenStack", "Ansible", "Terraform", "Slack", "ArcticDB" ], "continuousLearning" : "Coaching; Mentoring; Conference attendance; Academic qualifications; Professional qualifications", "problemSolvingSkills" : "Analytic approach", "qualificationsBasic" : "Expert in domain, Interest in financial markets, Agile development knowledge, Continuous integration knowledge, Code review knowledge, Unit testing knowledge, Refactoring knowledge, Python knowledge, Linux proficiency, Scripting languages knowledge, Data analysis techniques, NumPy/SciPy/Pandas knowledge, Mathematical knowledge, Statistics knowledge, Asset pricing theory knowledge, Optimisation algorithms knowledge", "qualificationsPreferred" : "Front office quantitative development experience, Web based development experience, Visualisation technology experience, Machine learning techniques experience, Natural language processing experience, Scikit-learn experience, Tensorflow experience", "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 The Role As a Quant Developer at Man Group you will be part of one of our flagship teams in Man’s systematic trading arm - Man AHL. The team works hand-in-hand with Quant Researchers focusing on equity market neutral models. Your challenges will be varied, and will involve building new alphas and new trading strategies. The Team Quant Developers at Man Group are all part of our broader technology team, members of a group of over sixty individuals representing eighteen nationalities. We have varied backgrounds including Computer Science, Mathematics, Physics, Engineering – even Classics - but what unifies us is a passion for technology and writing high-quality code. Our developers are organised into small cross-functional teams, with our engineering roles broadly of two kinds: “Quant Platform Developers” otherwise known as our “Core Techs”, and “Quant Developers” which we often refer to as “Sector Techs”. We use the term “Sector Tech” because some of our teams are aligned with a particular asset class or market sector. People often rotate teams in order to learn more about our system, as well as find the position that best matches their interests. Our Technology Our systems are almost all running on Linux and most of our code is in Python, with the full scientific stack: numpy, scipy, pandas, scikit-learn to name a few of the open-source libraries we use extensively. We implement the systems that require the highest data throughput in Java and C++. We use Airflow for workflow management, Kafka for data pipelines, Bitbucket for source control, Jenkins for continuous integration, Grafana + Prometheus for metrics collection, ELK for log shipping and monitoring, Docker and Kubernetes for containerisation, OpenStack for our private cloud, Ansible and Terraform for architecture automation, and Slack for internal communication. We heavily utilise ArcticDB (https://arcticdb.io/) our in-house developed DataFrame Database. Our technology list is never static: we constantly evaluate new tools and libraries. Technology and Business Skills At AHL we strive to hire only the brightest and best and most highly skilled and passionate technologists. Essential Exceptional technology skills; recognised by your peers as an expert in your domain A keen interest and understanding of financial markets and instruments A proponent of strong collaborative software engineering techniques and methods: agile development, continuous integration, code review, unit testing, refactoring and related approaches Strong knowledge of Python Proficient on Linux platforms with knowledge of various scripting languages Experience of data analysis techniques along with relevant libraries e. g. NumPy/SciPy/Pandas Relevant mathematical knowledge e. g. statistics, asset pricing theory, optimisation algorithms Advantageous Experience of front office quantitative software development e. g. in a hedge fund or investment bank Experience of web based development and visualisation technology for portraying large and complex data sets and relationships Experience of machine learning techniques, natural language processing and related libraries and frameworks e. g. scikit-learn, Tensorflow Personal Attributes Strong academic record and a degree with high mathematical and computing content e. g. Computer Science, Mathematics, Engineering or Physics from a leading university Craftsman-like approach to building software; takes pride in engineering excellence and instils these values in others Demonstrable passion for technology e. g. personal projects, open-source involvement Intellectually robust with a keenly analytic approach to problem solving Self-organised with the ability to effectively manage time across multiple projects and with competing business demands and priorities Focused on delivering value to the business with relentless efforts to improve process Strong interpersonal skills; able to establish and maintain a close working relationship with quantitative researchers, traders and senior business people alike Confident communicator; able to argue a point concisely and deal positively with conflicting views Working Here Man Group has a small company, no-attitude feel. It is flat structured, open, transparent and collaborative, and you will have plenty of opportunity to grow and have enormous impact on what we do. We are actively engaged with the broader technology community. We host and sponsor London’s PyData and Machine Learning Meetups We open-source some of our technology. See github.com/man-group We regularly talk at leading industry conferences, and tweet about relevant technology and how we’re using it. See @ManQuantTech We’re fortunate enough to have a fantastic open-plan office overlooking the River Thames, and continually strive to make our environment a great place in which to work. We believe that agile working allows us to deliver the best business outcomes for our clients and investors as well as having a positive impact on life / work balance and the wellbeing of our staff. We are simultaneously committed to \"levelling the playing field\" and believe that agile working promotes inclusivity across teams, regions and business units. We organise regular social events, everything from photography through climbing, karting, wine tasting and monthly team lunches We have annual away days and off-sites for the whole team As well as PC’s and Macs, in our office you’ll also find numerous pieces of cool tech such as light cubes and 3D printers, guitars, ping-pong and table-football, and a piano We offer competitive compensation, a generous holiday allowance, various health and other flexible benefits. We are also committed to continuous learning and development via coaching, mentoring, regular conference attendance and sponsoring academic and professional qualifications. 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" : "Quant Developer at Man Group. Skills: Quantitative development, Python, Linux, Data analysis. Build new alphas. Build new trading strategies", "postedDate" : "2026-06-13T21:02:50.559", "createdAt" : "2026-06-13T21:02:50.559", "lastUpdated" : "2026-06-15T03:43:46.444", "ingestTimestamp" : "2026-06-13T21:02:50.559", "mongoId" : "6a2c7c2b74d8ee00a094c828", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Data analysis techniques", "Mathematical knowledge", "Statistics", "Asset pricing theory", "Optimization algorithms", "Quantitative development", "Python", "Linux", "Data analysis", "Software engineering", "Asset pricing", "Agile development", "Financial markets", "Equity market neutral models", "Airflow", "Kafka", "Bitbucket", "Jenkins", "Grafana", "Prometheus", "ELK", "Docker", "Kubernetes", "OpenStack", "Ansible", "Terraform", "Slack", "ArcticDB" ], "skillCount" : 28, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 0.7777778, "_score" : 1129.7385, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2ca0f674d8ee00a09a3ed4", "title" : "Market Operations Specialist", "company" : "Novig", "industry" : "Markets", "salary" : { "min" : 70000.0, "max" : 90000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "New York, New York", "locations" : [ "New York, New York" ], "timestamp" : "2026-06-16T00:17:31.748", "fingerprint" : "d198d552bc1ccaf94e99544ac9d36f7b17b281a96dd398dca0136272d5d8c775", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/novig/2eddd226-7ee3-41f0-983c-4d0a9a36b744/application", "externalId" : "2eddd226-7ee3-41f0-983c-4d0a9a36b744", "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", "employmentType" : "FULL_TIME", "professionalSkills" : [ "Process management", "Cross-functional coordination", "Vendor management", "Stakeholder management", "Operational metrics", "Resource planning", "Continuous improvement" ], "hardSkillsList" : [ "Market creation", "Market curation", "Data-driven decisions" ], "hardSkills" : [ { "name" : "Market creation", "level" : "intermediate" }, { "name" : "Market curation", "level" : "intermediate" }, { "name" : "Data-driven decisions", "level" : "intermediate" } ], "majorSkills" : "Sports prediction markets, Market operations, Trading, Product development", "majorSkillsList" : [ "Sports prediction markets", "Market operations", "Trading", "Product development" ], "coreResponsibilities" : "Shape featured markets, Take prop requests, List new markets, Create and curate daily featured markets, Highlight compelling games, Highlight compelling matchups, Design creative markets, Collaborate with marketing, Maximize visibility, Make quick decisions, Make data-driven decisions, Engage directly with community, Interact with users on Discord, Gather prop requests from Discord, Answer user questions, Help bring new markets live, Share user feedback, Share competitive insights, Share ideas to improve platform, Ensure markets reflect fan conversations, Ensure markets reflect fan trends", "teamCollaboration" : "Cross-functionally with engineers; Cross-functionally with product; Cross-functionally with support teams", "domainKnowledge" : "Sports prediction markets; Sports trading; Major sports leagues; NFL; NCAAF; NBA; NHL; MLB; NCAAB; Soccer; UFC; Fan engagement; Trade deadlines; Free agency; Coaching changes; Player roles; Sports conversations; Sports trends", "domainList" : [ "sports-prediction-markets", "sports-trading", "major-sports-leagues", "nfl", "ncaaf", "nba", "nhl", "mlb", "ncaab", "soccer", "ufc", "fan-engagement", "trade-deadlines", "free-agency", "coaching-changes", "player-roles", "sports-conversations", "sports-trends" ], "domainSpecificKnowledge" : [ "Sports prediction markets", "Sports trading", "Major sports leagues", "NFL", "NCAAF", "NBA", "NHL", "MLB", "NCAAB", "Soccer", "UFC", "Fan engagement", "Trade deadlines", "Free agency", "Coaching changes", "Player roles", "Sports conversations", "Sports trends" ], "innovationCreativity" : "Build sports prediction markets from scratch; Decide what markets look like", "problemSolvingSkills" : "Data-driven decision making", "specialRequirements" : "Work evenings, Work weekends, Work nights", "qualificationsBasic" : "Sports fanatic, Trader's mindset, Product-oriented thinker, Deep knowledge of major sports leagues, Comfortable working during peak sports moments, Engaging directly with community, Gathering prop requests, Bringing new markets live quickly, Working cross-functionally with engineers, Working cross-functionally with product, Working cross-functionally with support teams, Sharing user feedback, Sharing competitive insights, Sharing ideas to improve platform, Tuned in to sports conversations, Tuned in to sports trends on social media, Help build future of sports prediction markets, Creating engaging trading experiences", "qualificationsPreferred" : "Technical background, Interested in building automation tools", "remoteFriendly" : false, "workSiteFlexibility" : "Hybrid", "rawDescription" : "MARKET OPERATIONS SPECIALIST $70k – $90k • meaningful equity ABOUT NOVIG Novig is building America's #1 sports prediction market. Our mission is to financialize and democratize sports trading - taking a closed system run by casinos and turning it into a fair, efficient, two-sided market where the power sits with users. With CFTC approval on the horizon, we're poised to go live across all 50 states as the leading sports-focused, federally regulated market built on trust, transparency, and real user protection. We're backed by some of Silicon Valley's top investors — Pantera, Forerunner, Lux, NFX, Paul Graham, and Joe Montana — who have collectively invested over $100M behind this vision. ABOUT THE ROLE You sit where sports meets markets. A star goes down in the third quarter, a trade rumor breaks at 11pm, a coach gets fired on a Tuesday - you decide what fans get to bet on and how fast it goes live. You shape the featured markets at the top of the app, take prop requests straight from the Discord, and list new ones while the conversation's still hot. You work when sports actually happen: game nights, Sunday afternoons, the overtime that runs past midnight. We're building sports prediction markets from scratch, and you get to decide what that looks like. This role lives at the intersection of trading, product, and sports with the opportunity to contribute at all levels of the business. WHO YOU ARE AND WHAT YOU WILL DO - You’re a sports fanatic with a trader’s mindset, excited to work at the intersection of sports, markets, and technology. - You are a product-oriented thinker with a deep knowledge of major sports leagues—including NFL, NCAAF, NBA, NHL, MLB, NCAAB, Soccer, and UFC—and understand the rhythms, storylines, and key moments that drive fan engagement. - You’re excited to create and curate daily featured markets, highlighting the most compelling games and matchups and shaping what users see at the top of the app. - You enjoy designing creative markets tied to major sports storylines—from trade deadlines and free agency to coaching changes and player roles—and collaborating with marketing to maximize visibility. - You thrive in fast-paced, real-time environments, making quick, data-driven decisions as games unfold and trading activity shifts. - You’re energized by engaging directly with a passionate community, interacting with users on Discord, gathering prop requests, answering questions, and helping bring new markets live quickly. - You’re comfortable working during peak sports moments, including evenings and weekends, when the most exciting games and trading activity happen. - You enjoy working cross-functionally with engineers, product, and support teams, sharing user feedback, competitive insights, and ideas to continuously improve the platform. - You’re highly tuned in to sports conversations and trends on social media, helping ensure markets reflect what fans are talking about in real time. - Most importantly, you’re excited to help build the future of sports prediction markets, creating engaging trading experiences for sports fans. - Bonus points if you have a technical background and are interested in building the automation tools that drive maximum efficiency and reduce manual workloads. WHY WORK HERE, IN THE WORDS OF THE PEOPLE WHO DO “I work with extremely stellar people, I own real systems, and decisions happen fast. No politics, no waiting for needless red tape. If something's broken, I fix it. If I build something good, it ships.” “The people! So smart, thoughtful, fun to work with, passionate about their craft, etc” “I'm having the most fun I've had in my entire career.” If you want responsibility, trust, and the chance to help build the future of sports prediction markets - take your shot, we’d love to connect. NOT FOR EVERYONE - Our work is tied to live sports - that means potential nights, weekends, and pressure included. - If you need clear swim lanes, a heavy process, or someone to tell you what to do, this won’t be the right environment. COMPENSATION & BENEFITS - $70k – $90k base, benchmarked at top-tier tech companies - Meaningful equity for every employee, regardless of role - 100% health premiums covered - 99% dental & vision covered - 401(k) with 4% company match - HSA + $1,080 annual company contribution - $50/monthly company contribution to employee transit - $27/day lunch stipend when working from our NYC office - $35/day dinner stipend when working from the NYC office after 6:30pm HOMEBASE Union Square, NYC In-person 4 days a week because we genuinely like being around each other.", "summaryDescription" : "Market Operations Specialist at Novig. Skills: Sports prediction markets, Market operations, Trading, Product development. Shape featured markets. 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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" : 1052.7671, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology" }, { "id" : "6a2c7c2b74d8ee00a094c82d", "title" : "Quant Research Analyst, Intern", "company" : "Man Group", "industry" : "Banking", "salary" : { "min" : 120000.0, "max" : 240000.0, "currency" : "CNY", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for intern roles in China's financial services industry, adjusted for entry-level seniority and company size." }, "location" : "China", "locations" : [ "China" ], "timestamp" : "2026-06-16T02:42:27.314", "fingerprint" : "93c05624890f8e8e952f1294aee9d72392f3e6310618f7d9499bf0c15dc96c0b", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/mangroup/jobs/4872158101", "externalId" : "4872158101", "industryFunction" : { }, "structuredLocations" : [ { "country" : "China", "continent" : "as", "workMode" : "onsite" } ], "locationText" : "China", "employmentType" : "INTERNSHIP", "remoteFriendly" : false, "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" : "Quant Research Analyst, Intern at Man Group", "postedDate" : "2026-06-14T20:05:46.240", "createdAt" : "2026-06-14T20:05:46.240", "lastUpdated" : "2026-06-16T02:42:27.314", "ingestTimestamp" : "2026-06-14T20:05:46.240", "mongoId" : "6a2c7c2b74d8ee00a094c82d", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Entry", "dataQualityScore" : 0.7777778, "_score" : 1024.1886, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Financial Services", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2aeb9974d8ee00a072ebdb", "title" : "Associate, E-Trading Quant", "company" : "Bank of America", "industry" : "Financial Services", "salary" : { "min" : 175000.0, "max" : 175000.0, "currency" : "USD", "frequency" : "yearly" }, "location" : "United States of America", "locations" : [ "United States of America" ], "timestamp" : "2026-06-14T23:37:36.355", "fingerprint" : "70fd9cf578a61ab68b2b4ee55da10e6db8fa95b2354e53f1c9132380931889ee", "source" : "workday", "language" : "en", "applyUrl" : "https://ghr.wd1.myworkdayjobs.com/Scoutt/job/New-York/Associate--E-Trading-Quant_26020133", "externalId" : "26020133", "industryFunction" : { }, "locationPoint" : "51.43667,5.97917", "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", "minimumEducation" : "Master's", "technicalSkills" : "Application Development, Artificial Intelligence, Machine Learning, Risk Analytics, Automation, Business Analytics, Risk Modeling", "professionalSkills" : [ "Financial analysis", "Quantitative analytics", "Complex modeling", "Analytic processes", "Systems approaches", "Quantitative methods", "Financial challenges", "Market trends", "Business problems", "Business transactions" ], "hardSkillsList" : [ "Financial analysis", "Quantitative analytics", "Complex modeling", "Risk modeling", "Trading analysis", "Investment analysis" ], "softSkillsList" : [ "Attention to Detail", "Innovative Thinking", "Prioritization", "Stakeholder Management", "Strategic Thinking", "Active Listening", "Oral Communications", "Problem Solving" ], "hardSkills" : [ { "name" : "Financial analysis", "level" : "intermediate" }, { "name" : "Quantitative analytics", "level" : "intermediate" }, { "name" : "Complex modeling", "level" : "intermediate" }, { "name" : "Risk modeling", "level" : "intermediate" }, { "name" : "Trading analysis", "level" : "intermediate" }, { "name" : "Investment analysis", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Attention to Detail" }, { "name" : "Innovative Thinking" }, { "name" : "Prioritization" }, { "name" : "Stakeholder Management" }, { "name" : "Strategic Thinking" }, { "name" : "Active Listening" }, { "name" : "Oral Communications" }, { "name" : "Problem Solving" } ], "majorSkills" : "Quantitative analytics, Complex modeling, Risk modeling", "majorSkillsList" : [ "Quantitative analytics", "Complex modeling", "Risk modeling" ], "coreResponsibilities" : "Perform financial analyses, Perform statistical analyses, Conduct quantitative analytics, Conduct complex modeling projects, Support development of new models, Support development of analytic processes, Support development of systems approaches, Determine solutions to solve business problems, Apply quantitative methods to financial challenges, Develop forecast models, Develop pricing models, Implement solutions for financial challenges, Conduct financial analyses, Prepare support documentation for client presentations, Assess market trends, Provide quantitative data to internal partners, Provide quantitative data to clients, Identify solutions required to solve business problems, Participate in client meetings, Participate in due diligence sessions, Participate in planning sessions, Identify cross-selling opportunities, Ensure seamless client delivery, Partner with various teams across the bank, Prepare recommendations on timing, Prepare recommendations on size, Prepare recommendations on structure of business transactions", "teamCollaboration" : "Partner with various teams; 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We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day. Being a Great Place to Work and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates’ physical, emotional, and financial wellness through affordable, competitive and flexible benefits. We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve. 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Key responsibilities include supporting in the development of new models, analytic processes, or systems approaches and determining solutions to solve business problems by applying quantitative methods to related financial challenges. **Responsibilities:** * Develops forecast and pricing models, analytic processes, or systems approaches, implementing solutions for financial challenges * Conducts financial analyses and prepares support documentation for client presentations * Assesses market trends and provides quantitative data to internal partners and clients to identify the solutions required to effectively solve business problems * Participates in client meetings, due diligence and planning sessions to identify cross-selling opportunities for team members and ensure seamless client delivery * Partners with various teams across the bank to prepare recommendations on timing, size, and structure of business transactions **Skills:** * Application Development * Artificial Intelligence/Machine Learning * Attention to Detail * Innovative Thinking * Risk Analytics * Automation * Business Analytics * Prioritization * Stakeholder Management * Strategic Thinking * Active Listening * Oral Communications * Problem Solving * Risk Modeling * Trading and Investment Analysis **Education:** Masters Degree in Computer Science, Economics, Mathematics or related field, OR related work experience **Hours Per Week:** 40 **Travel Required:** Yes, 5% of the time **Pay Transparency details** US - NY - New York - ONE BRYANT PARK - BANK OF AMERICA TOWER (NY1100) Pay and benefits information Pay range $175,000.00 - $175,000.00 annualized salary, offers to be determined based on experience, education and skill set. Discretionary incentive eligible This role is eligible to participate in the annual discretionary plan. Employees are eligible for an annual discretionary award based on their overall individual performance results and behaviors, the performance and contributions of their line of business and/or group; and the overall success of the Company. Benefits This role is currently benefits eligible. We provide industry-leading benefits, access to paid time off, resources and support to our employees so they can make a genuine impact and contribute to the sustainable growth of our business and the communities we serve.", "summaryDescription" : "Associate, E-Trading Quant at Bank of America. Skills: Quantitative analytics, Complex modeling, Risk modeling. Perform financial analyses. 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"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. 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At Coinbase, we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for \"good enough,\" you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase. Prediction markets are one of the fastest-growing areas in trading, offering traders a way to put money behind their beliefs in sports, politics, and culture. They can be powerful truth signals since traders have financial motivation to be right and there is no third party setting the odds with a built-in edge. As a Product Marketing Manager on the Consumer & Business team, you'll support the Prediction Markets team in growing awareness and adoption of Coinbase's prediction markets product. What you'll do: Own the voice of the customer by immersing yourself in the prediction markets ecosystem and understanding which segments of users are trading which types of prediction markets across sports, politics/economics, culture, and more. Develop growth strategies and tactics for ongoing news and big events (e.g., sports tournaments, elections), ideating, refining, and executing plans using channels like social, email/push, influencers, paid ads, events, and incentives. Lead go-to-market strategy for product and feature launches such as parlays, from planning through execution. Measure and report on the performance of product marketing initiatives to inform ongoing strategy. Think big about the future of prediction markets and how Coinbase can use them to better predict outcomes and bring awareness to those predictions. Required Skills and Experience: 5+ years of marketing experience within the trading/crypto or FinTech space. Demonstrated track record of ideating and implementing growth strategies on products. Demonstrated track record of creating customer segmentation and insights. Advanced quantitative and deductive skills, with the ability to distinguish between signal and noise and make data-guided decisions. Demonstrated ability to collaborate effectively across multiple teams to drive go-to-market execution. Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality. P77089 #LI-Remote Pay Transparency Notice: Base salary varies by location (see range below). Total compensation may also include equity and bonus eligibility, and benefits (medical, dental, vision, 401(k)). Annual base salary range (excluding equity and bonus): $140,080—$164,800 USD Please be advised that each candidate may submit a maximum of four applications within any 30-day period. We encourage you to carefully evaluate how your skills and interests align with Coinbase's roles before applying. Commitment to Equal Opportunity Coinbase is proud to be an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, sex, gender expression or identity, sexual orientation or any other basis protected by applicable law. Coinbase will also consider for employment qualified applicants with criminal histories in a manner consistent with applicable federal, state and local law. For US applicants, you may view the Employee Rights and the Know Your Rights notices by clicking on their corresponding links. Additionally, Coinbase participates in the E-Verify program in certain locations, as required by law. Coinbase is also committed to providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of a disability for any part of the employment process, please contact us at accommodations[at]coinbase.com to let us know the nature of your request and your contact information. For quick access to screen reading technology compatible with this site click here to download a free compatible screen reader (free step by step tutorial can be found here). Global Data Privacy Notice for Job Candidates and Applicants Depending on your location, the General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA) 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. By submitting your application, you are agreeing to our use and processing of your data as required. For US applicants only, by submitting your application you are agreeing to arbitration of disputes as outlined here. AI Disclosure For select roles, Coinbase is piloting an AI tool based on machine learning technologies to conduct initial screening interviews to qualified applicants. The tool simulates realistic interview scenarios and engages in dynamic conversation. A human recruiter will review your interview responses, provided in the form of a voice recording and/or transcript, to assess them against the qualifications and characteristics outlined in the job description. For select roles, Coinbase is also piloting an AI interview intelligence platform to transcribe and summarize interview notes, allowing our interviewers to fully focus on you as the candidate. The above pilots are for testing purposes and Coinbase will not use AI to make decisions impacting employment. To request a reasonable accommodation due to disability, please contact accommodations[at]coinbase.com", "summaryDescription" : "Product Marketing Manager, Prediction Markets at Coinbase. Skills: Product marketing, Growth marketing, Prediction markets. Own voice of customer. Understand user segments", "postedDate" : "2026-06-11T23:22:53.601", "createdAt" : "2026-06-11T23:22:53.601", "lastUpdated" : "2026-06-14T21:44:28.217", "ingestTimestamp" : "2026-06-11T23:22:53.601", "mongoId" : "6a2a751974d8ee00a0656bdb", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 135000, "salaryAnnualMax" : 195000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Quantitative analysis", "Deductive reasoning", "Product marketing", "Growth marketing", "Prediction markets", "Growth strategies", "Customer segmentation", "Data-guided decisions", "Trading", "Crypto", "FinTech" ], "skillCount" : 11, "jobCategory" : "marketing", "jobSubcategory" : "marketing-&-communications", "dataQualityScore" : 0.8888889, "_score" : 967.79474, "daysOld" : 2, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "FinTech" }, { "id" : "6a2c5ddf74d8ee00a08df2d9", "title" : "Quantic - Quantitative Researcher Intern (Summer 2027)", "company" : "Walleye Capital", "industry" : "Financial Services", "salary" : { "min" : 20000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Boston, Massachusetts, United States", "locations" : [ "Boston", "Massachusetts", "United States" ], "timestamp" : "2026-06-14T19:02:26.948", "fingerprint" : "da92600827cfc79114162473fe27e610e42a2435b4bcbfdfd4697a6ae4b0d1df", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/walleyecapital-external-students/jobs/4679173006", "externalId" : "4679173006", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Boston", "state" : "Massachusetts", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "42.3588336,-71.0578303" } ], "locationText" : "Boston, Massachusetts, United States", "employmentType" : "INTERNSHIP", "technicalSkills" : "Python, R, LLM", "professionalSkills" : [ "Quantitative trading", "Quantitative research", "Portfolio optimization", "Systematic investing" ], "hardSkillsList" : [ "Statistical modeling", "Computational methods", "Machine learning", "Optimization", "Time-series analysis", "Predictive signals", "Data analysis" ], "softSkillsList" : [ "Creativity", "Initiative", "Teamwork", "Curiosity", "Intellectual humility" ], "hardSkills" : [ { "name" : "Statistical modeling", "level" : "intermediate" }, { "name" : "Computational methods", "level" : "intermediate" }, { "name" : "Machine learning", "level" : "intermediate" }, { "name" : "Optimization", "level" : "intermediate" }, { "name" : "Time-series analysis", "level" : "intermediate" }, { "name" : "Predictive signals", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Creativity" }, { "name" : "Initiative" }, { "name" : "Teamwork" }, { "name" : "Curiosity" }, { "name" : "Intellectual humility" } ], "majorSkills" : "Quantitative research, Machine learning, Data analysis", "majorSkillsList" : [ "Quantitative research", "Machine learning", "Data analysis" ], "coreResponsibilities" : "Research predictive signals, Design predictive signals, Test predictive signals, Research data sets, Design data sets, Test data sets, Research trading strategies, Design trading strategies, Test trading strategies, Extract large datasets, Analyze large datasets, Apply statistical methods, Apply computational methods, Enhance research infrastructure, Enhance research tools, Develop machine learning models, Design scalable code, Implement scalable code, Work in Python, Work in R, Contribute to research tools, Contribute to research libraries, Leverage AI tools, Enhance processes with AI, Enhance analyses with AI", "teamCollaboration" : "Collaborative culture; Cross-disciplinary exchange", "domainKnowledge" : "Quantitative trading; Financial markets; Systematic investing; Asset returns; Portfolio management", "domainList" : [ "quantitative-trading", "financial-markets", "systematic-investing", "asset-returns", "portfolio-management" ], "domainSpecificKnowledge" : [ "Quantitative trading", "Financial markets", "Systematic investing", "Asset returns", "Portfolio management" ], "toolProficiency" : [ "LLM-based analytical pipelines" ], "continuousLearning" : "Continuous learning", "innovationCreativity" : "Innovation; Creativity", "problemSolvingSkills" : "Tackle complex problems; Analytical thinking", "outcomesObjectives" : "Impact trading profits", "qualificationsBasic" : "Pursuing undergraduate or advanced degree, Expected graduation date between Dec 2027 and June 2028, Programming skills in Python or R, Experience with large datasets, APIs, or databases, Rigorous analytical thinking, Statistical modeling abilities, Familiarity with machine learning, optimization, or time-series analysis", "qualificationsPreferred" : "PhD preferred", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Position: Quantic - Quantitative Researcher Intern (Summer 2027) Location: Boston, MA Please apply to only one opportunity between the Quantitative Developer, Quantitative Researcher and PhD Quantitative Researcher positions with Quantic. If the team finds you could be a potential fit for the other, we will contact you. 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 Quant, Fundamental Equities, and Volatility strategies. Our Team Overview: Walleye Capital is seeking highly quantitative and creative Quantitative Researcher Interns to work in the rapidly growing Quantic team based out of Boston. Quantic is Walleye’s principal quantitative investment business, established in 2016 as one of its core investment strategies. Quantic has subsequently evolved into one of the most successful trading teams in the industry. We are a tight-knit, collaborative, and intellectually rigorous group of scientists, engineers, and traders leveraging advanced statistical modeling techniques to identify and capitalize on profitable trading opportunities in global equities, options, and futures. What sets Quantic apart is our pragmatic, engineering-driven culture, where achieving goals—and achieving them the right way—takes precedence. We foster collaboration among colleagues, confident that the best ideas arise through cross-disciplinary exchange. Our commitment to continuous self-reflection and growth drives us to build the strongest possible platform for our team's future success. We are seeking talented researchers to help elevate our capabilities and join us on this journey. This role offers the opportunity to engage directly with cutting-edge data analysis, portfolio optimization, platform development, and operation of fully automated trading systems. You will join a team where your creativity, initiative, and teamwork will make direct impacts on trading profits for our investors. We invite researchers with a proven record of innovation and achievement in their fields to apply. Position Overview: As a Quantic Intern, you’ll work directly with experienced team members on meaningful projects that impact trading strategies and operations. You’ll have the opportunity to work on high-impact initiatives and develop your skills in a dynamic setting where innovation, teamwork, and talent drive success. We are seeking students with strong technical backgrounds (e.g., mathematics, statistics, computer science, or engineering), demonstrated initiative, and an interest in quantitative trading and research. Successful interns are curious, collaborative, and eager to tackle complex problems in a fast-paced, supportive environment. The internship is 10 weeks in length and will take place in Boston from June to August 2027. Responsibilities: Research, design, and test predictive signals, data sets, and systematic trading strategies. Extract and analyze large datasets from structured and unstructured sources, applying advanced statistical and computational methods. Enhance research infrastructure and tools for trading, risk management and attribution. Develop machine learning models to predict patterns in asset returns, risks, trading costs, or other portfolio-relevant variables. Design and implement scalable code across various stages of the investment process. Work in Python and/or R, with opportunities to contribute to research tools and libraries. Leverage AI tools including LLM-based analytical pipelines to enhance processes and analyses. We seek individuals who: Are pursuing an undergraduate or advanced degree in computer science, engineering, statistics, mathematics, or a related field, with an expected graduation date between December 2027 and June 2028. Possess strong programming skills—particularly in Python or R—and hold experience working with large datasets, APIs, or databases. Demonstrate rigorous analytical thinking, statistical modeling abilities, and familiarity with techniques from machine learning, optimization, or time-series analysis. Are self-starters who enjoy digging into complex, open-ended problems and can work both independently and collaboratively with a team. Exhibit a genuine interest in financial markets, systematic investing, AI/LLM application, and using technology in dynamic, data-rich environments. Showcase creativity and enthusiasm for leveraging AI tools to enhance productivity, improve processes, and generate investment alpha. Thrive in a collaborative culture that values intellectual humility, creativity, and continuous learning. Pay Range: The expected monthly pay for this position is $20,000/month. Interns will also receive a $10,000 housing stipend and transportation to and from Boston (domestic travel only). The deadline to apply for this opportunity is Friday, July 31 at 11:59pm ET. For questions about the process, please review our Campus FAQs. Please apply to only one opportunity between the Quantitative Developer, Quantitative Researcher and PhD Quantitative Researcher positions with Quantic. If the team finds you could be a potential fit for the other, we will contact you. 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" : "Quantic - Quantitative Researcher Intern (Summer 2027) at Walleye Capital. Skills: Quantitative research, Machine learning, Data analysis. Research predictive signals. Design predictive signals", "postedDate" : "2026-06-12T21:36:17.563", "createdAt" : "2026-06-12T21:36:17.563", "lastUpdated" : "2026-06-14T19:02:26.948", "ingestTimestamp" : "2026-06-12T21:36:17.563", "mongoId" : "6a2c5ddf74d8ee00a08df2d9", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 240000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Statistical modeling", "Computational methods", "Machine learning", "Optimization", "Time-series analysis", "Predictive signals", "Data analysis", "Creativity", "Initiative", "Teamwork", "Curiosity", "Intellectual humility", "Quantitative research", "Quantitative trading", "Portfolio optimization", "Systematic investing", "Financial markets", "Asset returns", "Portfolio management", "LLM-based analytical pipelines" ], "skillCount" : 20, "jobCategory" : "other", "jobSubcategory" : "quantic", "dataQualityScore" : 0.8888889, "_score" : 924.20636, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Financial Services" }, { "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" : 922.23303, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c5ddf74d8ee00a08df2cc", "title" : "Equity Volatility Quant Researcher Intern (Summer 2027)", "company" : "Walleye Capital", "industry" : "Investment Management", "salary" : { "min" : 5000.0, "max" : 5000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Miami, Florida, United States", "locations" : [ "Miami", "Florida", "United States" ], "timestamp" : "2026-06-15T00:13:02.410", "fingerprint" : "a867a4e7cd9f4457e8015b87c4e1d8385db10b900e74a48769e140fb4ceed4b8", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/walleyecapital-external-students/jobs/4676334006", "externalId" : "4676334006", "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" : "INTERNSHIP", "technicalSkills" : "Python, AI", "professionalSkills" : [ "Quantitative research", "Trading decisions", "Risk management" ], "hardSkillsList" : [ "Probability", "Statistics", "Time-series analysis", "Machine learning", "Optimization" ], "softSkillsList" : [ "Analytical thinking", "Intellectual curiosity", "Creativity", "Enthusiasm", "Intellectual humility" ], "hardSkills" : [ { "name" : "Probability", "level" : "intermediate" }, { "name" : "Statistics", "level" : "intermediate" }, { "name" : "Time-series analysis", "level" : "intermediate" }, { "name" : "Machine learning", "level" : "intermediate" }, { "name" : "Optimization", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Analytical thinking" }, { "name" : "Intellectual curiosity" }, { "name" : "Creativity" }, { "name" : "Enthusiasm" }, { "name" : "Intellectual humility" } ], "coreResponsibilities" : "Build foundation in options markets, Keep up to date on macro developments, Understand implications for trading decisions, Collaborate with portfolio managers, Collaborate with quantitative researchers, Perform quantitative research tasks, Enhance research infrastructure, Enhance research tools", "teamCollaboration" : "Collaborate with portfolio managers; Collaborate with quantitative researchers; Work independently; Work collaboratively with a team", "domainKnowledge" : "Options markets; Volatility strategies; Single-stock options; Index options", "domainList" : [ "options-markets", "volatility-strategies", "single-stock-options", "index-options" ], "domainSpecificKnowledge" : [ "Options markets", "Volatility strategies", "Single-stock options", "Index options" ], "toolProficiency" : [ "APIs", "Databases" ], "continuousLearning" : "Continuous learning", "problemSolvingSkills" : "Complex, open-ended problems", "qualificationsBasic" : "Pursuing undergraduate or non-MBA advanced degree, Expected graduation date between December 2027 and June 2028, Programming skills in Python, Experience working with large datasets, Experience working with APIs, Experience working with databases, Rigorous analytical thinking, Knowledge of probability & statistics, Knowledge of time-series analysis, Knowledge of machine learning, Knowledge of optimization", "qualificationsPreferred" : "Genuine interest in financial markets, Genuine interest in risk taking, Genuine interest in using technology, Creativity for leveraging AI tools, Enthusiasm for leveraging AI tools, Thrive in collaborative culture, Intellectual humility, Continuous learning", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Position: Equity Volatility Quant Researcher Intern (Summer 2027) Location: Miami, FL 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 Fundamental Equities, Quant, and Volatility 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. Position Overview: Walleye Capital is seeking exceptional Quant Researcher Interns to join its longest-standing business, Equity Volatility, for Summer 2027. We make markets in U. S. single stock and index options, running a diverse set of strategies – systematic and discretionary, grounded in both quantitative rigor and qualitative insight. With a strong foundation, our group operates at the frontier of innovation – continually evolving our strategies and infrastructure as the options landscape grows in scale, complexity, and opportunity. This high-impact internship is designed for deeply analytical, technically adept students with a strong intellectual curiosity about options markets. Interns will play a meaningful role in advancing quantitative research projects that drive real-world trading decisions. Structured to reflect the responsibilities of a full-time quant researcher, the program offers immersive, hands-on exposure to our end-to-end research and trading workflows, providing an authentic and rigorous experience at the intersection of theory and execution. The internship is 10 weeks in length and will take place in Miami from June to August 2027. Responsibilities: Build a strong foundation in options markets through both an academic and a practitioner’s lens. Keep up to date on major macro developments and market-moving headlines, with a focus on understanding their implications for trading decisions and portfolio risk. Collaborate with seasoned portfolio managers and quantitative researchers specializing in single-stock and index volatility strategies. Perform various quantitative research tasks and projects using large-scale volatility datasets. Enhance research infrastructure and tools for trading and risk management, with an emphasis on leveraging AI. We seek individuals who: Are pursuing an undergraduate or non-MBA advanced degree in a quantitative field, with an expected graduation date between December 2027 and June 2028. Possess strong programming skills—particularly in Python —and hold experience working with large datasets, APIs, or databases. Demonstrate rigorous analytical thinking with a strong knowledge of probability & statistics (time-series analysis, machine learning, optimization). Are self-starters who enjoy digging into complex, open-ended problems and can work both independently and collaboratively with a team. Exhibit a genuine interest in financial markets, risk taking, and using technology in dynamic, data-rich environments. Showcase creativity and enthusiasm for leveraging AI tools to enhance productivity and improve processes and workflows. Thrive in a collaborative culture that values intellectual humility, creativity, and continuous learning. Pay Range: The expected pay for this position is $50,000 for 10 weeks. Interns will also receive a $10,000 housing stipend and transportation to and from Miami (domestic travel only). The deadline to apply for this opportunity is Friday, July 31 at 11:59pm ET. For questions about the process, please review our Campus FAQs. 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" : "Equity Volatility Quant Researcher Intern (Summer 2027) at Walleye Capital. Build foundation in options markets. 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Being a bit weird, we - Are self-taught; our founders do not come from any of the big HFTs - Chose to have no VCs on cap-table; this spot is for our colleagues - Made Bratislava the central hub, not London or Amsterdam CULTURE When you do something you love, it does not feel like work. At Wincent work is purposeful and fulfilling. INTEGRITY IS NOT NEGOTIABLE Handshakes are sacred for us. Being in the money making business is good, but that alone is not worth our soul; we follow the motto “Be the good guys in the market”. SAY THINGS AS THEY ARE Life is too short for games of politics, fluff, or bullshit in general. TRUST EACH OTHER We embrace internal radical transparency in terms of compensation, bonuses, and trading strategie QUANT RESEARCH/TRADING INTERNSHIP - SUMMER 2027 WITH RELOCATION PROVIDED Would you like to be paired with experienced traders who will teach you how to identify market signals, analyze and execute trading strategies, conduct statistical analysis, construct quantitative models, and enhance your trading intuition? If you answered \"YES,\" we've got something special for you: Join us as a Quantitative Research/Trading Intern on-site in Bratislava, Slovakia. We support European and UK citizens with accommodation & travel arrangements. You'll dive into the exciting world of cryptocurrency trading, gain hands-on experience in quantitative analysis, algorithm development, and market research. As a Quant Intern, you'll have the opportunity to contribute to real projects, learn from experienced quant traders, and gain practical experience to get a head start on your trading career. Working on projects alongside mentors will give you a sense of the variety of problems we solve every day. Throughout the summer, you'll also participate in simulated interactive mock trading sessions. Apply today to join our Quantitative Research/Trading team. ABOUT THE QUANT RESEARCH/TRADING TEAM Our trading team digs into fresh trading ideas and tweaks the ones we already have. Most of our trading is fully automated, but we're not afraid to mix in some gut feeling or out-of-the-box ideas if they seem promising. A solid trader usually rocks a mix of strong technical skills (think stats and basic coding) and a good feel for probabilities and expected values. WHAT WILL YOU DO IN THE QUANT RESEARCH/TRADING TEAM We’ve structured the program to be both fun and challenging, with a typical day including: - Morning betting games to get the day started. - Discussions on trading-related topics to deepen your understanding of market dynamics. - Work on practical exercises that mirror actual quant and trading tasks. - Time to explore your own ideas and projects, supported by our experienced team. - Play various games to enhance your trading intuition. On top of that, you will: - Work with Python, Pandas, SQL, and Grafana for data analysis and real-time monitoring. - Learn trading fundamentals from experienced quants and traders. - Collaborate in teams to tackle challenging open-ended quant problems suitable for all levels, including beginners. - Participate in discussions about the problems to sharpen your argumentation skills. - Experience manual trading with substantial, yet manageable positions to grasp market dynamics. WHAT WE EXPECT FROM YOU - Love for games or betting. - Basic coding skills in Python or similar languages, with a willingness to learn and adapt to new technologies. - Strong communication and collaboration skills. - Curiosity and enthusiasm for cryptocurrency markets, with a desire to learn and grow in a fast-paced environment. ON-SITE IN SLOVAKIA - RELOCATION PROVIDED - This internship opportunity is on-site in Bratislava, Slovakia, with relocation provided. - Internships are NOT open to remote work. INTERVIEW PROCESS - Online Math test: Low-to-medium complexity problems focused on probability, logic, and mathematical skills. This is a take-home challenge that you can do anytime in your free time. - Quant Interview 45min: A set of medium complexity problems to assess your intuition and problem-solving approach. - Quant Interview 90min: General discussion about your background and passions, followed by medium-hard complexity problems to assess your intuition and problem-solving approach. - On-site Interview: Engage in a set of betting games to evaluate your quantitative reasoning and decision-making skills. You'll conduct the final rounds on-site in Bratislava, Slovakia. All costs are covered and you'll get to know the team, city, and our venues. COMPENSATION AND WORK ARRANGEMENT - Salary: 5,000 EUR / month which is an equivalent of earning €13,105 in London according to livingcost.org. https://livingcost.org/cost/bratislava/london due to low living costs and low income taxes in Slovakia, see below. - Full-day catering: All-inclusive breakfast, lunch, afternoon snacks, fruits, and other treats in our offices save you hundreds of euros every month. - Travel, Accommodation, and Visa Support: We'll help you cover the costs of joining us on-site. - Potential for Full-Time Transition: Exceptional interns may be considered for full-time positions based on their performance and our business needs. - Commitment: Full-time commitment for the duration of the seven-week summer 2027 internship. - On-site: Participation in our offices in Bratislava, Slovakia, is required to facilitate continuous interaction and learning with the team. We will support accommodation arrangements. - Onboarding: You will receive comprehensive training and guidance from our team, with introductory tasks designed to help you quickly grasp quantitative trading concepts and methodologies. WHY TO CHOOSE BRATISLAVA OVER OTHER LOCATIONS - Low living costs: Bratislava offers a significantly lower cost of living compared to most major European cities (source: Numbeo). - Low income tax: Slovakia offers only 25% personal income tax, compared to 55% Austria, 50% Belgium, 49% Netherlands, 48% Portugal, 47% Spain, 45% UK, France, and Germany, 44% Greece, and 40% Ireland according to taxsummaries.pwc.com http://taxsummaries.pwc.com. - Regional hub: Bratislava lies at the intersection of Austria (only 80km from Vienna), Czechia (130km from Brno), and Hungary (200km from Budapest). - Safety: Bratislava is one of the safest capitals in Europe, providing peace of mind that is harder to find in larger cities with higher crime rates, such as Paris, London, or Brussels. - High quality of life: Bratislava offers a balanced lifestyle with access to nature, excellent public amenities, and shorter commutes, unlike many larger cities where high living costs often compromise quality of life. - Booming economy and opportunities: Bratislava is a growing economic hub with a focus on technology, finance, and innovation, attracting international companies and startups. Don't hesitate and apply today! WORKING AT WINCENT At Wincent, we foster a culture of transparency, ownership, and autonomy, where every team member is empowered to make a meaningful impact. We prioritize clear objectives and give you the freedom to innovate and grow within a supportive, high-performing environment. We value exceptional TOP 1% talent over a perfect match to a job description. If our vision and values resonate with you, we’d love to hear from you. Don’t hesitate to reach out—let’s explore how you can be part of shaping the future of cryptocurrency trading with us!", "summaryDescription" : "Quantitative Research Internship at Wincent. Skills: Quantitative research, Trading, Data analysis. Identify market signals. 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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. 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Founded in 2005 as an options market maker, we have organically grown into a global investment firm specializing in Fundamental Equities, Quant, and Volatility 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. Position Overview: Walleye Capital is seeking Volatility Trading Developer Interns for Summer 2027 to support the Equity Volatility business. As an intern, you’ll work closely with Volatility traders, software developers, quants, and operational teams to help develop and optimize tools that support daily trading operations and infrastructure. You’ll tackle real-world challenges, help ideate and design creative solutions, and learn how a volatility trading business functions from end-to-end. This internship offers the opportunity to enhance your skill set through hands-on, high-impact projects and direct mentorship. The internship is 10 weeks in length and will take place in New York City from June to August 2027. Responsibilities: Collaborate with traders to help implement and scale trading strategies, build bespoke datasets, automate execution workflows, and develop tools that integrate trading signals into the execution stack. Design and maintain tools supporting daily trading inputs, including earnings, dividends, interest rates, and quant model parameters; design and manage critical trade lifecycle processes, including Early Exercise and Expiration workflows. Assist in modernizing legacy systems across risk, P leverage AI tools to enhance productivity, drive efficiency, and improve workflows. Are self-motivated, adaptable, and detail-oriented, with the ability to manage multiple priorities in a fast-paced environment. Communicate ideas clearly and effectively, both in writing and verbally, while maintaining accuracy and thoroughness. Thrive in a collaborative culture that values intellectual humility, creativity, and continuous learning. Pay Range: The expected monthly pay for this position is $14,000/month. Interns will also receive a $10,000 housing stipend and transportation to and from New York City (domestic travel only). The deadline to apply for this opportunity is Friday, July 31 at 11:59pm ET. For questions about the process, please review our Campus FAQs. 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 Trading Developer Intern (Summer 2027) at Walleye Capital. Skills: Volatility trading, Software development, Quant strategy. Implement trading strategies. Scale trading strategies", "postedDate" : "2026-06-12T21:48:26.603", "createdAt" : "2026-06-12T21:48:26.603", "lastUpdated" : "2026-06-15T00:27:32.054", "ingestTimestamp" : "2026-06-12T21:48:26.603", "mongoId" : "6a2c5ddf74d8ee00a08df2e8", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 168000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Data implementation", "Workflow automation", "Dataset building", "System modernization", "AI tool leverage", "Adaptability", "Accuracy", "Thoroughness", "Intellectual humility", "Creativity", "Continuous learning", "Volatility trading", "Software development", "Quant strategy", "Execution workflow", "Trade lifecycle", "Risk management", "Equity volatility", "Options market making", "Quant strategies", "Earnings", "Dividends", "Interest rates", "Quant model design", "Early Exercise", "Expiration workflows", "Risk systems", "P&L systems" ], "skillCount" : 28, "jobCategory" : "other", "jobSubcategory" : "single-stock---volatility", "dataQualityScore" : 0.8888889, "_score" : 903.9456, "daysOld" : 2, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Financial Services" }, { "id" : "6a2c5ddf74d8ee00a08df2d6", "title" : "Quantic - PhD Quantitative Researcher Intern (Summer 2027)", "company" : "Walleye Capital", "industry" : "Financial Services", "salary" : { "min" : 20000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Boston, Massachusetts, United States", "locations" : [ "Boston", "Massachusetts", "United States" ], "timestamp" : "2026-06-15T00:27:57.063", "fingerprint" : "d68017c232568f5d3dcacf1b14f69e2968b7c2c180cbcf609ba8d725da17f4b8", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/walleyecapital-external-students/jobs/4679184006", "externalId" : "4679184006", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Boston", "state" : "Massachusetts", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "42.3588336,-71.0578303" } ], "locationText" : "Boston, Massachusetts, United States", "employmentType" : "INTERNSHIP", "minimumEducation" : "PhD", "technicalSkills" : "Python, R, SQL, Spark, dbt, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Delta Lake, scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, SageMaker, Athena, GCP, Vertex AI, Azure, Synapse, ML Studio", "professionalSkills" : [ "Quantitative analysis", "Portfolio optimization", "Trading strategies", "Risk management", "Systematic investing", "Financial markets" ], "hardSkillsList" : [ "Statistical modeling", "Machine learning", "Optimization", "Time-series analysis", "Data analysis", "Predictive modeling" ], "softSkillsList" : [ "Curious", "Creative", "Initiative", "Teamwork", "Intellectual humility", "Continuous learning" ], "hardSkills" : [ { "name" : "Statistical modeling", "level" : "intermediate" }, { "name" : "Machine learning", "level" : "intermediate" }, { "name" : "Optimization", "level" : "intermediate" }, { "name" : "Time-series analysis", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Predictive modeling", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Curious" }, { "name" : "Creative" }, { "name" : "Initiative" }, { "name" : "Teamwork" }, { "name" : "Intellectual humility" }, { "name" : "Continuous learning" } ], "majorSkills" : "Quantitative research, Machine learning, Data analysis", "majorSkillsList" : [ "Quantitative research", "Machine learning", "Data analysis" ], "coreResponsibilities" : "Research predictive signals, Design predictive signals, Test predictive signals, Research data sets, Design data sets, Test data sets, Research trading strategies, Design trading strategies, Test trading strategies, Extract large datasets, Analyze large datasets, Apply statistical methods, Apply computational methods, Enhance research infrastructure, Enhance trading tools, Enhance risk management tools, Enhance attribution tools, Develop machine learning models, Predict asset returns, Predict portfolio risks, Predict trading costs, Design scalable code, Implement scalable code, Work in Python, Work in R, Contribute to research tools, Contribute to research libraries, Leverage AI tools, Enhance processes with LLMs, Enhance analyses with LLMs", "teamCollaboration" : "Tight-knit group; Cross-disciplinary exchange; Collaborative culture", "domainKnowledge" : "Quantitative trading; Financial markets; Systematic investing; AI/LLM application; Options market making; Volatility strategies; Global equities; Options; Futures", "domainList" : [ "quantitative-trading", "financial-markets", "systematic-investing", "ai-llm-application", "options-market-making", "volatility-strategies", "global-equities", "options", "futures" ], "domainSpecificKnowledge" : [ "Quantitative trading", "Financial markets", "Systematic investing", "AI/LLM application", "Options market making", "Volatility strategies", "Global equities", "Options", "Futures" ], "toolProficiency" : [ "LLM" ], "continuousLearning" : "Continuous self-reflection; Continuous growth", "innovationCreativity" : "Creativity; Initiative; Innovation", "problemSolvingSkills" : "Complex problems", "outcomesObjectives" : "Impact trading profits; Elevate capabilities", "workSiteFlexibility" : "Onsite", "rawDescription" : "Position: Quantic - PhD Quantitative Researcher Intern (Summer 2027) Location: Boston, MA Please apply to only one opportunity between the Quantitative Developer, Quantitative Researcher and PhD Quantitative Researcher positions with Quantic. If the team finds you could be a potential fit for the other, we will contact you. 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 Quant, Fundamental Equities, and Volatility strategies. Our Team Overview: Walleye Capital is seeking highly quantitative and creative PhD Quantitative Researcher Interns to work in the rapidly growing Quantic team based out of Boston. Quantic is Walleye’s principal quantitative investment business, established in 2016 as one of its core investment strategies. Quantic has subsequently evolved into one of the most successful trading teams in the industry. We are a tight-knit, collaborative, and intellectually rigorous group of scientists, engineers, and traders leveraging advanced statistical modeling techniques to identify and capitalize on profitable trading opportunities in global equities, options, and futures. What sets Quantic apart is our pragmatic, engineering-driven culture, where achieving goals—and achieving them the right way—takes precedence. We foster collaboration among colleagues, confident that the best ideas arise through cross-disciplinary exchange. Our commitment to continuous self-reflection and growth drives us to build the strongest possible platform for our team's future success. We are seeking talented researchers to help elevate our capabilities and join us on this journey. This role offers the opportunity to engage directly with cutting-edge data analysis, portfolio optimization, platform development, and operation of fully automated trading systems. You will join a team where your creativity, initiative, and teamwork will make direct impacts on trading profits for our investors. We invite researchers with a proven record of innovation and achievement in their fields to apply. Position Overview: As a Quantic Intern, you’ll work directly with experienced team members on meaningful projects that impact trading strategies and operations. You’ll have the opportunity to work on high-impact initiatives and develop your skills in a dynamic setting where innovation, teamwork, and talent drive success. We are seeking students with strong technical backgrounds (e.g., mathematics, statistics, computer science, or engineering), demonstrated initiative, and an interest in quantitative trading and research. Successful interns are curious, collaborative, and eager to tackle complex problems in a fast-paced, supportive environment. The internship is 10 weeks in length and will take place in Boston from June to August 2027. Responsibilities: Research, design, and test predictive signals, data sets, and systematic trading strategies. Extract and analyze large datasets from structured and unstructured sources, applying advanced statistical and computational methods. Enhance research infrastructure and tools for trading, risk management and attribution. Develop machine learning models to predict patterns in asset returns, risks, trading costs, or other portfolio-relevant variables. Design and implement scalable code across various stages of the investment process. Work in Python and/or R, with opportunities to contribute to research tools and libraries. Leverage AI tools including LLM-based analytical pipelines to enhance processes and analyses. We seek individuals who: Are pursuing a PhD degree in computer science, engineering, statistics, operations research, mathematics, or a related field, with an expected graduation date between December 2027 and June 2028. Possess strong programming skills—particularly in Python or R—and hold experience working with large datasets, APIs, or databases. Demonstrate rigorous analytical thinking, statistical modeling abilities, and familiarity with techniques from machine learning, optimization, or time-series analysis. Are self-starters who enjoy digging into complex, open-ended problems and can work both independently and collaboratively with a team. Exhibit a genuine interest in financial markets, systematic investing, AI/LLM application, and using technology in dynamic, data-rich environments. Showcase creativity and enthusiasm for leveraging AI tools to enhance productivity, improve processes, and generate investment alpha. Thrive in a collaborative culture that values intellectual humility, creativity, and continuous learning. Pay Range: The expected monthly pay for this position is $20,000/month. Interns will also receive a $10,000 housing stipend and transportation to and from Boston (domestic travel only). The deadline to apply for this opportunity is Friday, October 30 at 11:59pm ET. For questions about the process, please review our Campus FAQs. Please apply to only one opportunity between the Quantitative Developer, Quantitative Researcher and PhD Quantitative Researcher positions with Quantic. If the team finds you could be a potential fit for the other, we will contact you. 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" : "Quantic - PhD Quantitative Researcher Intern (Summer 2027) at Walleye Capital. Skills: Quantitative research, Machine learning, Data analysis. Research predictive signals. Design predictive signals", "postedDate" : "2026-06-12T21:55:00.303", "createdAt" : "2026-06-12T21:55:00.303", "lastUpdated" : "2026-06-15T00:27:57.063", "ingestTimestamp" : "2026-06-12T21:55:00.303", "mongoId" : "6a2c5ddf74d8ee00a08df2d6", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 240000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Statistical modeling", "Machine learning", "Optimization", "Time-series analysis", "Data analysis", "Predictive modeling", "Curious", "Creative", "Initiative", "Teamwork", "Intellectual humility", "Continuous learning", "Quantitative research", "Quantitative analysis", "Portfolio optimization", "Trading strategies", "Risk management", "Systematic investing", "Financial markets", "Quantitative trading", "AI/LLM application", "Options market making", "Volatility strategies", "Global equities", "Options", "Futures", "LLM" ], "skillCount" : 27, "jobCategory" : "other", "jobSubcategory" : "quantic", "dataQualityScore" : 0.8888889, "_score" : 870.0714, "daysOld" : 2, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Financial Services" }, { "id" : "6a3062cef292fd229cf9b53d", "title" : "Trade Marketing Manager", "company" : "Orbico Hungary", "industry" : "Food And Beverages", "salary" : { "min" : 1.2E7, "max" : 1.8E7, "currency" : "HUF", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Trade Marketing Manager in Budapest, Hungary, adjusted for the FMCG industry and company size." }, "location" : "Budapest, HU", "locations" : [ "Budapest", "HU" ], "timestamp" : "2026-06-16T11:46:32.093", "fingerprint" : "a8940a6992eb9dd04f5977c6bc0b505141995ee08e9807149445cb9a21852325", "source" : "smartrecruiters", "language" : "en", "applyUrl" : "https://jobs.smartrecruiters.com/OrbicoHungary1/744000132183979-trade-marketing-manager-retail-divizio", "externalId" : "744000132183979", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Budapest", "country" : "Hungary", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "47.4813896,19.1457723" } ], "locationText" : "Budapest, Hungary", "employmentType" : "FULL_TIME", "minimumEducation" : "Higher education degree", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "mid", "technicalSkills" : "Excel, MS Word, MS PowerPoint, MS Outlook, Canva", "professionalSkills" : [ "Data analysis", "Forecasting", "Stock management", "Inventory management", "Reporting", "Presentation preparation" ], "hardSkillsList" : [ "Trade marketing", "Brand management", "Profitability management", "Marketing spend management", "New product launches", "Market analysis", "Consumer research", "Sales forecasting", "Stock level management", "Aging inventory handling", "Sales toolkit preparation", "Distribution planning", "Pricing strategy", "Activity planning", "Marketing material preparation", "In-store placement guidelines", "Sales team training", "Report preparation", "Presentation preparation", "Reconciliation", "Accruals" ], "softSkillsList" : [ "Negotiation", "Problem-solving" ], "hardSkills" : [ { "name" : "Trade marketing", "level" : "intermediate" }, { "name" : "Brand management", "level" : "intermediate" }, { "name" : "Profitability management", "level" : "intermediate" }, { "name" : "Marketing spend management", "level" : "intermediate" }, { "name" : "New product launches", "level" : "intermediate" }, { "name" : "Market analysis", "level" : "intermediate" }, { "name" : "Consumer research", "level" : "intermediate" }, { "name" : "Sales forecasting", "level" : "intermediate" }, { "name" : "Stock level management", "level" : "intermediate" }, { "name" : "Aging inventory handling", "level" : "intermediate" }, { "name" : "Sales toolkit preparation", "level" : "intermediate" }, { "name" : "Distribution planning", "level" : "intermediate" }, { "name" : "Pricing strategy", "level" : "intermediate" }, { "name" : "Activity planning", "level" : "intermediate" }, { "name" : "Marketing material preparation", "level" : "intermediate" }, { "name" : "In-store placement guidelines", "level" : "intermediate" }, { "name" : "Sales team training", "level" : "intermediate" }, { "name" : "Report preparation", "level" : "intermediate" }, { "name" : "Presentation preparation", "level" : "intermediate" }, { "name" : "Reconciliation", "level" : "intermediate" }, { "name" : "Accruals", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Negotiation" }, { "name" : "Problem-solving" } ], "majorSkills" : "Trade marketing, Brand strategy, Campaign management, Growth metrics", "majorSkillsList" : [ "Trade marketing", "Brand strategy", "Campaign management", "Growth metrics" ], "coreResponsibilities" : "Prepare annual strategic plan, Manage turnover, Manage profitability, Manage DPSM principles, Manage marketing spend, Monitor new product launches, Execute new product launches, Analyze market effectiveness, Analyze trade marketing effectiveness, Conduct consumer research, Participate in forecasting, Align with other departments, Manage stock levels, Handle aging inventory, Prepare sales toolkit, Ensure stock availability, Support product launches, Support sales, Collaborate with departments, Collaborate with agencies, Ensure report preparation, Ensure presentation preparation, Ensure documentation preparation, Organize promotions, Coordinate promotions, Organize events, Coordinate events, Prepare reconciliations, Prepare accruals, Provide in-store placement guidelines, Train sales team, Manage Trade Marketing Assistant, Motivate Trade Marketing Assistant, Develop Trade Marketing Assistant", "teamCollaboration" : "Other departments; Agencies; Sales team", "domainKnowledge" : "FMCG; Retail channels; HoReCa channels", "domainList" : [ "fmcg", "retail-channels", "horeca-channels" ], "domainSpecificKnowledge" : [ "FMCG", "Retail channels", "HoReCa channels" ], "toolProficiency" : [ "Excel", "Canva" ], "communicationSkills" : "Negotiation skills", "documentationSkills" : "Report preparation; Presentation preparation", "continuousLearning" : "Continuous learning opportunities; Participation in trainings", "problemSolvingSkills" : "Problem-solving skills", "specialRequirements" : "Company car", "qualificationsBasic" : "Higher education degree, Minimum 5 years of experience, Fluent English, User-level computer skills, Advanced Excel knowledge", "qualificationsPreferred" : "Experience in handling agencies, Creativity, Proactivity, Ability to work independently, Analytical mindset, Market research skills", "remoteFriendly" : false, "workSiteFlexibility" : "Flexible", "rawDescription" : "Are you energized by the fast-paced world of FMCG and passionate about working with products found in every household? Would you like to be part of a leading distribution company in Europe? Orbico is currently one of Europe’s leading distribution companies, operating in 20 countries with nearly 9,000 colleagues. We ensure that over 500 of the world’s best-known global and local brands (including Lavazza coffee, Pringles, Kellogg’s, Lipton, Saga, Mutti, Jana, and Milka chocolate drink) reach consumers through retail and HoReCa channels. We are looking for a new team member to join the Orbico Hungary Retail team in a Trade Marketing Manager position. * Prepare the annual strategic plan for trade marketing activities. * Manage the turnover, profitability (up to GM level), implementation and support of DPSM principles, and marketing spend of the assigned brand. * Monitor and execute plans provided by the principal for new product launches. * Analyze the market and the effectiveness of trade marketing activities. * Conduct research on target consumer groups and purchasing habits as needed. * Actively participate in the forecasting process, align with other departments, manage stock levels and handle aging inventory. * Prepare the toolkit for the sales team (plans, listings, distribution, pricing, activities, marketing materials) and ensure stock availability to support launches, product penetration and sales. * Collaborate with other departments and agencies. * Ensure the preparation of reports, presentations and other necessary documentation. * Monitor and execute plans provided by the principal for new product launches. * Actively participate in the forecasting process, align with other departments, manage stock levels and handle aging inventory. * Organize and coordinate promotions and events as needed. * Prepare reconciliations and accruals. * Provide guidelines for in-store placements and train the sales team. * Manage, motivate and develop the Trade Marketing Assistant supporting your area. ## Qualifications * Higher education degree * Minimum 5 years of experience in a similar position * Experience in handling agencies, strong communication skills * Creativity, proactivity, ability to work independently * Fluent English (negotiation level) * Confident, strong Excel skills enabling efficient and fast data analysis * Outstanding communication, problem-solvin and negotiation skills * Strong logical, mathematical, and strategic thinking skills * Analytical mindset * User-level computer skills (MS Word, PPT, Outlook, Canva) * Advanced Excel knowledge * Market research and analytical skills ## Additional Information * A dynamically growing international company representing premium brands * Continuous learning opportunities and participation in trainings * Diverse career opportunities * Multinational environment with flexible and fast decision-making * Supportive team and management * Home office opportunity * Wide range of benefits (cafeteria, study support, language learning support, unlimited mobile data, significant discounts on premium products distributed by us) * Healthcare services * Performance-based bonus system * Mobile phone * Company car with private use option – free within a defined monthly limit, with cost reimbursement in case of exceeding * Regular team-building programs and professional community events", "summaryDescription" : "Trade Marketing Manager at Orbico Hungary. Skills: Trade marketing, Brand strategy, Campaign management, Growth metrics. Prepare annual strategic plan. 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Skills: Market research, Data analysis, Quantitative analysis. Conduct market research studies. 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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. 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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. 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The team consists of Quantitative Researchers and Quantitative Developers to research, define, and implement models that will guide clients in portfolio construction, asset allocation, and risk management. The team members have diverse backgrounds such as math, physics, economics, quantitative finance, computer science, and other science and engineering fields, and collaborate closely with business-side colleagues, platform architects, software developers, and product managers to deliver analytics through the software platform for the firm’s clients. The Quant Developers have a core mission of developing robust and scalable quantitative models to deliver portfolio risk analytics capabilities as part of the firm’s commercial technology platform for financial advisors and asset managers. The team members will implement statistical, machine learning, and quantitative financial models, applied to a combination of proprietary, public, and third-party data, to deliver analytics for multi-asset portfolios including alternative assets. Responsibilities Develop robust and scalable quantitative financial models and collaborate closely with quant researchers to produce proprietary risk analytics models as part of the firm’s software platform. Test, validate, and document quantitative methodologies to ensure accuracy, robustness, and transparency. Develop centralized financial calculation engines powering the firm’s commercial technology platform. Document and communicate quantitative methodologies and analytics to others including stakeholders and clients. Collaborate with other teams to ensure risk analytics are delivered through the software platform with excellent user experience. Collaborate regularly with other stakeholders and partners to solicit requirements, seek feedback and provide updates. Qualifications 8+ years of professional experience in quantitative financial modeling, data science, or software development Strong programming skills in Python for data analysis, modeling, and software development Strong problem-solving and communication skills, with the ability to explain technical concepts to non-technical audiences Able to work in a dynamic and fast-paced environment Knowledge of JAVA/Scala/C++ is a plus Distributed Systems experience is a plus Experience with cloud services is a plus Benefits The base salary range for this role is $180,000 to $210,000 depending on level. iCapital offers a compensation package which includes salary, equity for all full-time employees, and an annual performance bonus. Employees also receive a comprehensive benefits package that includes an employer matched retirement plan, generously subsidized healthcare with 100% employer paid dental, vision, telemedicine, and virtual mental health counseling, parental leave, and unlimited paid time off (PTO). We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office Monday-Thursday, with the flexibility to work remotely on Friday. For additional information on iCapital, please visit https://www.icapitalnetwork.com/about-us Twitter: @icapitalnetwork | LinkedIn: https://www.linkedin.com/company/icapital-network-inc | Awards Disclaimer: https://www.icapitalnetwork.com/about-us/recognition/ iCapital is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.", "summaryDescription" : "Quant Engineer - Vice President at iCapital", "postedDate" : "2026-06-15T23:28:21.834", "createdAt" : "2026-06-15T23:28:21.834", "lastUpdated" : "2026-06-16T07:59:59.027", "ingestTimestamp" : "2026-06-15T23:28:21.834", "mongoId" : "6a3066aef292fd229cfb45fb", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 180000, "salaryAnnualMax" : 210000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "VP", "dataQualityScore" : 0.8888889, "_score" : 844.3968, "daysOld" : 0, "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. 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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. 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Product; Engineering; Comms; Growth; Design; BD; Community leads; Channel owners", "projectManagementSkills" : [ "Roadmap planning" ], "domainKnowledge" : "Agentic L1; Prediction protocol; Real-time settlement; AI resolution; Agentic liquidity; On-chain UX; CLOB; AMM; Token incentive design; Web3 product; Web3 space; Hyper-performance L1; Decentralized products; On-chain applications; DEX; Prediction Protocols; Metaverse Network; Morpheus Technology; AI inference; 2026 peak-fragility market", "domainList" : [ "agentic-l1", "prediction-protocol", "real-time-settlement", "ai-resolution", "agentic-liquidity", "on-chain-ux", "clob", "amm", "token-incentive-design", "web3-product", "web3-space", "hyper-performance-l1", "decentralized-products", "on-chain-applications", "dex", "prediction-protocols", "metaverse-network", "morpheus-technology", "ai-inference", "2026-peak-fragility-market" ], "domainSpecificKnowledge" : [ "Agentic L1", "Prediction protocol", "Real-time settlement", "AI resolution", "Agentic liquidity", "On-chain UX", "CLOB", "AMM", "Token incentive design", "Web3 product", "Web3 space", "Hyper-performance L1", "Decentralized products", "On-chain applications", "DEX", "Prediction Protocols", "Metaverse Network", "Morpheus Technology", "AI inference", "2026 peak-fragility market" ], "toolProficiency" : [ "Notion", "Slack", "X" ], "communicationSkills" : "Written English; Spoken English; Thought leadership", "documentationSkills" : "Launch threads; Research notes; Explainer videos; KOL kits; AMA narratives", "specialRequirements" : "UK-friendly timezone", "outcomesObjectives" : "Turn protocol into brand; Measurable post-launch impact", "qualificationsBasic" : "5+ years product marketing, 2+ years consumer web3 product, Crypto-native, Shipped GTM Web3 product", "qualificationsPreferred" : "Direct experience prediction markets, Public footprint in crypto, Worked through token launch, Built agent-based products, Shipped AI-native products", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "About Somnia: SOMNIA is the Agentic Chain - a hyper-performance L1 operating at an order of magnitude faster than existing networks. We empower builders and traders to create real-time, autonomous, and fully decentralized products, powered by agents, that were previously impossible and cannot be built anywhere else. It’s where the future of Web3 protocols will be built, so we’re facilitating a new wave of on-chain applications from DEX to Prediction Protocols and much, much more. Somnia is being developed by Somnia Foundation backed by Improbable https://www.improbable.io/, a British tech Unicorn +++ that has been at the forefront of building virtual worlds for over a decade. Somnia received initial funding from MSquared https://www.msquared.io/, which raised $150 million https://www.businesswire.com/news/home/20220407005101/en/Improbable-Raises-US150m-to-Establish-M%C2%B2-MSquared-a-Metaverse-Network-and-Ecosystem-Powered-by-Its-Morpheus-Technology from a16z crypto, SoftBank, Mirana Ventures, CMT Digital, and SIG. About the Role: Prophecy is Somnia's prediction protocol - a flagship product designed to prove what an Agentic L1 actually unlocks: sub-second markets, AI-resolved outcomes, and autonomous agents trading information at machine speed. Prophecy enables prediction markets to be real-time, agent-native, and an order of magnitude faster than any incumbent is today. We're hiring a Product Marketing Manager to own how Prophecy shows up in the world. You'll be the connective tissue between product, growth, comms, and community, translating a deeply technical edge into positioning that traders, builders, and partners immediately get. You'll own the narrative, lead every launch, and run the experiments that turn a new prediction protocol into a category-defining brand. This is a builder's role, not a steward's. You'll be writing the playbook. The team is small, decisions are fast, and the work shows up in market within weeks. Up for shaping the next chapter of on-chain prediction markets? Let's talk. Key Responsibilities: - Own positioning and messaging for Prophecy end-to-end: what it is, who it's for, why it's different, and why now. Translate technical primitives (real-time settlement, AI resolution, agentic liquidity) into sharp, defensible narratives that work across trader, builder, and partner audiences. - Lead go-to-market for every Prophecy launch: mainnet milestones, new market categories, agent integrations, partner activations, and token / incentive moments. Run cross-functional launch pods spanning product, engineering, comms, growth, design, and BD. - Define and run the marketing roadmap for Prophecy in lockstep with the product and community leads. Sequence launches, campaigns, and content so each beat compounds on the last instead of competing for airtime. - Build the audience. Design and execute always-on programs that grow Prophecy's qualified builders base. - Own competitive intelligence. Maintain a live read on the competitive landscape such that you understand how to differentiate and position Prophecy - Run customer and market research. Talk to traders, builders, and KOLs continuously. Bring insight back into product roadmap, pricing, and creative. - Brief and produce content that earns attention in the web3 space: launch threads, longform research notes, explainer videos, dashboards, KOL kits, conference assets, and AMA narratives. Quality bar is \"screenshotted on CT,\" not \"ticked the box.\" - Partner with comms on tier-1 press, podcast bookings, and thought leadership. Land Prophecy in the publications and shows the target audience actually reads and listens to. - Instrument everything. Define the KPIs that matter and own the weekly reporting rhythm. Kill what isn't working, double down on what is. - Be the channel partner-in-chief internally. Brief channel owners on the Prophecy narrative so every channel ships consistent, on-message activations without you in the room. Requirements: - 5+ years in product marketing, with at least 2 spent on a consumer-facing web3 product (prediction markets, derivatives DEX, perps, options, equities trading, or fintech with a trader audience). - Crypto-native. You hold a wallet, understand on-chain UX, know the difference between a CLOB and an AMM, can read a token incentive design, and have shipped GTM for at least one Web3 product that hit market. - Track record of owning launches end-to-end. From positioning brief through measurable post-launch impact. Bring 2-3 launches you can talk through in detail: the thesis, the bets, the numbers, and what you'd do differently. - Sharp narrative instinct. You can take a 40-page technical spec and produce a 280-character hook that builders share. Writing samples will be requested. - Quantitative fluency. Comfortable with numbers, you frame every campaign around hypotheses and read the data yourself rather than waiting for analytics. - Operator mindset. You're a maker, not a manager. You ship the brief, write the thread, edit the deck, and chase the asset. Comfortable with ambiguity, allergic to process for its own sake. - Cross-functional gravity. You can hold the line on a launch narrative with founders, product leads, designers, and BD without losing the room. Strong opinions, loosely held, clearly argued. - Excellent written and spoken English. This role lives in Notion, Slack, X, and on calls with global partners. NICE TO HAVE - Direct experience with prediction markets. - A public footprint in crypto (CT, Mirror, podcast appearances, conference talks) that signals fluency with the audience you'll be marketing to. - Worked through a token launch (TGE, season, airdrop) on the GTM side. - Built or shipped agent-based / AI-native consumer products. Why Join Somnia? Design The Future: Join Somnia to work remotely with a global team, earn competitive compensation with token incentives, and help build the future of Web3 at a company where your impact truly matters. First of its Kind: Make Somnia famous as the only hyperspeed L1 with native AI inference. High Stakes: Influence a brand targeting a $1M+ launch budget in the 2026 peak-fragility market. Incentives: Competitive salary + tokens. Role Location The role is remote, but we are looking for someone based on a UK-friendly timezone (+/- 4 hours). Reporting Lines This role reports directly to the GM for Prophecy and functionally to the Head of Marketing, Somnia Foundation.", "summaryDescription" : "Product Marketing Manager, Prophecy at Somnia. Skills: Product marketing, Web3, Prediction markets. Own positioning and messaging. 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External partners; International trade marketing colleagues; Internal stakeholders", "projectManagementSkills" : [ "Project management", "Stakeholder management" ], "domainKnowledge" : "FMCG; Foodservice channel; Customer journeys; Content performance", "domainList" : [ "fmcg", "foodservice-channel", "customer-journeys", "content-performance" ], "domainSpecificKnowledge" : [ "FMCG", "Foodservice channel", "Customer journeys", "Content performance" ], "toolProficiency" : [ "Google Ads" ], "documentationSkills" : "Copywriting; Content editing", "continuousLearning" : "Test-and-learn mindset; Continuous improvement; Experimentation; Optimisation", "innovationCreativity" : "AI; Automation", "problemSolvingSkills" : "Translate insights into actions; Recommend improvements; Optimise results", "outcomesObjectives" : "Drive distribution; Drive rate of sale; Drive penetration; Drive engagement; Drive conversion; Drive retention; Influence purchase decisions; Increase end user awareness; Increase new business conversion; Improve efficiency; Improve speed of execution; Improve marketing personalisation", "qualificationsBasic" : "Experience in digital trade marketing, Hands-on delivery across channels, Understanding of digital marketing fundamentals, Working knowledge of SEO, Working knowledge of technical website best practices, Working knowledge of key digital platforms, Experience working closely with customers, Project management skills, Stakeholder management skills, Copywriting skills, Content editing skills, Confident using insights and performance data, Excellent organisational skills, Attention to detail, Proactive, test-and-learn mindset", "qualificationsPreferred" : "Experience in FMCG environment", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "This is an exciting opportunity to join a well-established branded business with ambitious growth plans. You will play an important role in delivering and optimising digital activity across owned and paid channels, while helping to improve how we use data, automation and new technology to engage customers more effectively. The Digital Trade Marketing Executive is responsible for driving demand and accelerating sales through digital-first trade marketing initiatives across the foodservice channel. This role sits at the intersection of sales, marketing, and customers (distributors, wholesalers, and end users such as pubs, QSRs and restaurants), ensuring that brand strategies are translated into commercially effective trade activations. The position requires strong collaboration with internal teams (sales, category, marketing, supply chain) and external partners (distributors, buying groups, and key operators), with a focus on measurable ROI and execution excellence. * Develop and implement digital trade marketing plans aligned with commercial and category growth targets, translating strategies into impactful campaigns that drive distribution, rate of sale and penetration * Deliver and optimise customer lifecycle marketing across the UK & Ireland, including lead generation, CRM journeys, marketing automation and multi-channel campaigns (email, SMS, WhatsApp) to drive engagement, conversion and retention * Drive Aviko’s brand visibility and conversion across wholesaler digital touchpoints, optimising use of retailer portals, e-commerce platforms and CMS to influence purchase decisions at the point of choice * Lead trade marketing with key customers, strengthening Aviko’s branded presence across their digital channels to increase end user awareness and new business conversion * Collaborate with international trade marketing colleagues to share best practices and localise global initiatives for the UK & Ireland market * Lead Search Everywhere Optimisation (SEO, GEO, SGE & AEO) and support Google Ads campaigns, including setup, optimisation, reporting and performance improvement * Monitor, analyse and report on digital KPIs, translating insights into clear actions, opportunities and next steps * Support integrated digital campaigns aligned with broader brand and commercial priorities, working closely with internal stakeholders and external partners to maximise execution and visibility * Identify and leverage opportunities in AI and automation to improve efficiency, speed of execution and marketing personalisation. ## Qualifications * Experience in a digital trade marketing role within an FMCG environment, with hands-on delivery across channels such as website content, SEO, email, paid search, and campaign reporting. * Strong understanding of digital marketing fundamentals, including customer journeys, content performance and lead generation * Working knowledge of SEO, technical website best practices and key digital platforms such as GA4, Google Tag Manager and Google Ads * Experience working closely with customers, understanding their business needs and translating these into effective trade marketing solutions that drive category growth * Strong project and stakeholder management skills, with the ability to manage multiple priorities effectively * Strong copywriting and content editing skills for digital channels * Confident in using insights and performance data to recommend improvements and optimise results. * Excellent organisational skills and attention to detail * A proactive, test-and-learn mindset with a focus on continuous improvement through experimentation and optimisation.", "summaryDescription" : "Digital Trade Marketing Executive at Aviko. Skills: Digital trade marketing, Customer acquisition, Campaign management, Growth metrics. Develop digital trade marketing plans. Implement digital trade marketing plans", "postedDate" : "2026-06-15T13:44:01.000", "createdAt" : "2026-06-16T00:26:07.527", "lastUpdated" : "2026-06-16T10:52:34.647", "ingestTimestamp" : "2026-06-16T00:26:07.527", "mongoId" : "6a306b0cf292fd229cfcf1c7", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "30k-50k", "hasSalary" : false, "allSkills" : [ "SEO", "GEO", "SGE", "AEO", "Paid search", "Digital trade marketing", "Customer acquisition", "Campaign management", "Growth metrics", "Trade marketing", "Customer lifecycle marketing", "Lead generation", "Marketing automation", "Campaign reporting", "Performance improvement", "Stakeholder management", "Project management", "FMCG", "Foodservice channel", "Customer journeys", "Content performance", "Google Ads" ], "skillCount" : 22, "jobCategory" : "marketing", "jobSubcategory" : "growth", "seniorityLevel" : "Mid", "dataQualityScore" : 1.0, "_score" : 796.9019, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Food & Beverage", "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" : 794.91235, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2a5c0874d8ee00a0612988", "title" : "Equity L/S Desk Quant Analyst", "company" : "Verition Fund Management LLC", "industry" : "Financial Services", "salary" : { "min" : 150000.0, "max" : 200000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Miami, Florida, United States", "locations" : [ "Miami", "Florida", "United States", "New York", "NY", "USA" ], "certifications" : [ "CFA", "FRM" ], "timestamp" : "2026-06-14T21:21:39.612", "fingerprint" : "51f7fe429908dbd2726b429782d31de5def48a67c1ec35bce925a7a021c7a2aa", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://www.verition.com/open-positions?gh_jid=5159866007", "externalId" : "5159866007", "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", "technicalSkills" : "Python, R, C++, SQL, Java", "professionalSkills" : [ "Quantitative analysis", "Financial modeling", "Risk management", "Portfolio construction" ], "hardSkillsList" : [ "Statistical modeling", "Machine learning", "Data analysis" ], "softSkillsList" : [ "Adaptability", "Intellectual curiosity" ], "hardSkills" : [ { "name" : "Statistical modeling", "level" : "intermediate" }, { "name" : "Machine learning", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Adaptability" }, { "name" : "Intellectual curiosity" } ], "majorSkills" : "Quantitative analysis, Equity markets, Financial modeling", "majorSkillsList" : [ "Quantitative analysis", "Equity markets", "Financial modeling" ], "coreResponsibilities" : "Develop quantitative trading strategies, Build and maintain trading models, Analyze market data, Implement trading algorithms, Monitor trading performance, Collaborate with portfolio managers, Conduct research on market trends", "teamCollaboration" : "Portfolio managers; Traders; Research analysts", "domainKnowledge" : "Equity markets; Derivatives; Fixed income; Risk methodologies", "domainList" : [ "equity-markets", "derivatives", "fixed-income", "risk-methodologies" ], "domainSpecificKnowledge" : [ "Equity markets", "Derivatives", "Fixed income", "Risk methodologies" ], "toolProficiency" : [ "Bloomberg Terminal", "FactSet" ], "problemSolvingSkills" : "Analytical skills", "qualificationsBasic" : "5+ years experience", "qualificationsPreferred" : "coding assistants experience", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Verition Fund Management LLC (“Verition”) is a multi-strategy, multi-manager hedge fund founded in 2008. Verition focuses on global investment strategies including Global Credit, Global Convertible, Volatility hands-on experience with coding assistants such as Claude Code or comparable tools is a meaningful advantage. A strong sense of ownership and urgency, with the grit to dig into problems and see solutions through. A can-do approach, intellectual curiosity, adaptability, and a genuine passion for equity markets and investing. Salary Range $150,000—$200,000 USD", "summaryDescription" : "Equity L/S Desk Quant Analyst at Verition Fund Management LLC. Skills: Quantitative analysis, Equity markets, Financial modeling. Develop quantitative trading strategies. Build and maintain trading models", "postedDate" : "2026-06-11T19:49:19.538", "createdAt" : "2026-06-11T19:49:19.538", "lastUpdated" : "2026-06-14T21:21:39.612", "ingestTimestamp" : "2026-06-11T19:49:19.538", "mongoId" : "6a2a5c0874d8ee00a0612988", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 150000, "salaryAnnualMax" : 200000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Statistical modeling", "Machine learning", "Data analysis", "Adaptability", "Intellectual curiosity", "Quantitative analysis", "Equity markets", "Financial modeling", "Risk management", "Portfolio construction", "Derivatives", "Fixed income", "Risk methodologies", "CFA", "FRM", "Bloomberg Terminal", "FactSet" ], "skillCount" : 17, "jobCategory" : "other", "jobSubcategory" : "equity-l/s", "dataQualityScore" : 0.7777778, "_score" : 789.63043, "daysOld" : 3, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Financial Services" }, { "id" : "6a2c5ddf74d8ee00a08df2c9", "title" : "Central Equity Quant Research (CEQR) Intern (Summer 2027)", "company" : "Walleye Capital", "industry" : "Financial Services", "salary" : { "min" : 20000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "New York, New York, United States", "locations" : [ "New York", "New York", "United States" ], "timestamp" : "2026-06-15T00:49:10.960", "fingerprint" : "24f4108ce6481f3c887307d88e470ad4d70be36635c90ddc3bf567b17b56c50b", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/walleyecapital-external-students/jobs/4676069006", "externalId" : "4676069006", "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" : "INTERNSHIP", "technicalSkills" : "R, Python, AI, LLM", "professionalSkills" : [ "Quantitative research", "Model performance evaluation", "Predictive modeling", "Explanatory modeling", "Statistical ranking", "Calibration frameworks", "Unstructured data synthesis", "Investment strategies", "Trading decisions", "Risk management", "Attribution", "Systematic investing" ], "hardSkillsList" : [ "Mathematical modeling", "Data analysis", "Programming", "Statistical analysis" ], "softSkillsList" : [ "Creativity", "Intellectual humility", "Continuous learning" ], "hardSkills" : [ { "name" : "Mathematical modeling", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Programming", "level" : "intermediate" }, { "name" : "Statistical analysis", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Creativity" }, { "name" : "Intellectual humility" }, { "name" : "Continuous learning" } ], "majorSkills" : "Quantitative analysis, Data analysis, Programming, AI/LLM application", "majorSkillsList" : [ "Quantitative analysis", "Data analysis", "Programming", "AI/LLM application" ], "coreResponsibilities" : "Conduct quantitative research, Evaluate model performance, Identify opportunities for improvement, Build predictive models, Build explanatory models, Identify patterns in asset returns, Identify patterns in risks, Identify patterns in trading costs, Identify patterns in price impact, Identify patterns in portfolio management, Build statistical ranking models, Build calibration frameworks, Build structured approaches to synthesizing unstructured data, Gain exposure to strategies, Collaborate across groups, Integrate work into production systems, Support trading decisions, Build infrastructure for trading, Enhance infrastructure for trading, Build infrastructure for risk management, Enhance infrastructure for risk management, Build infrastructure for attribution, Enhance infrastructure for attribution, Leverage AI tools, Leverage LLM-based analytical pipelines", "teamCollaboration" : "Collaborate closely with investment teams; Work independently and collaboratively", "domainKnowledge" : "Financial markets; Execution trading; Quantitative investment", "domainList" : [ "financial-markets", "execution-trading", "quantitative-investment" ], "domainSpecificKnowledge" : [ "Financial markets", "Execution trading", "Quantitative investment" ], "innovationCreativity" : "Leveraging AI tools to enhance productivity; Leveraging AI tools to improve processes; Leveraging AI tools to generate investment alpha", "problemSolvingSkills" : "Digging into complex, open-ended problems", "qualificationsBasic" : "Undergraduate or advanced degree in computer science, engineering, statistics, mathematics, or related field, Expected graduation date between December 2027 and June 2028, Quantitative and analytical skills, Programming proficiency in R and/or Python", "qualificationsPreferred" : "PhD preferred, Specific ML framework experience, Cloud platform certs", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Position: Central Equity Quant Research (CEQR) Intern (Summer 2027) Location: New York, NY 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 Fundamental Equities, Quant, and Volatility 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. Position Overview: Walleye Capital is seeking highly quantitative and analytical interns to join our Central Equity Quant Research (CEQR) team for Summer 2027. As a CEQR intern, you’ll work at the core of our firm’s trading infrastructure, developing and optimizing models that reduce trading costs and decipher short-term alphas. You’ll contribute to projects that influence our quantitative investment strategies and collaborate closely with our investment teams. This is a unique opportunity for quantitative minds who thrive at the intersection of mathematical modeling, data analysis, and programming. The internship is 10 weeks in length and will take place in New York City from June to August 2027. Responsibilities: Conduct quantitative research to evaluate model performance and identify opportunities for improvement using large-scale datasets. Build predictive and explanatory models to identify patterns in asset returns, risks, trading costs and price impact, or other aspects relevant to managing our portfolios, including statistical ranking models, calibration frameworks, and structured approaches to synthesizing unstructured data. Gain exposure to a range of strategies and collaborate across groups to integrate your work into production systems that support trading decisions. Help build and enhance our infrastructure and tools for trading, risk management and attribution, leveraging AI tools including LLM-based analytical pipelines. We seek individuals who: Are pursuing an undergraduate or advanced degree in computer science, engineering, statistics, mathematics, or a related field, with an expected graduation date between December 2027 and June 2028. Demonstrate strong quantitative and analytical skills (including programming proficiency in R and/or Python). Are self-starters who enjoy digging into complex, open-ended problems and can work both independently and collaboratively with a team. Exhibit a genuine interest in financial markets, execution trading, systematic investing, AI/LLM application, and using technology in dynamic, data-rich environments. Showcase creativity and enthusiasm for leveraging AI tools to enhance productivity, improve processes, and generate investment alpha. Thrive in a collaborative culture that values intellectual humility, creativity, and continuous learning. Pay Range: The expected monthly pay for this position is $20,000/month. Interns will also receive a $10,000 housing stipend and transportation to and from New York City (domestic travel only). The deadline to apply for this opportunity is Friday, July 31 at 11:59pm ET. For questions about the process, please review our Campus FAQs. 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" : "Central Equity Quant Research (CEQR) Intern (Summer 2027) at Walleye Capital. Skills: Quantitative analysis, Data analysis, Programming, AI/LLM application. Conduct quantitative research. Evaluate model performance", "postedDate" : "2026-06-12T21:43:57.651", "createdAt" : "2026-06-12T21:43:57.651", "lastUpdated" : "2026-06-15T00:49:10.960", "ingestTimestamp" : "2026-06-12T21:43:57.651", "mongoId" : "6a2c5ddf74d8ee00a08df2c9", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 240000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Mathematical modeling", "Data analysis", "Programming", "Statistical analysis", "Creativity", "Intellectual humility", "Continuous learning", "Quantitative analysis", "AI/LLM application", "Quantitative research", "Model performance evaluation", "Predictive modeling", "Explanatory modeling", "Statistical ranking", "Calibration frameworks", "Unstructured data synthesis", "Investment strategies", "Trading decisions", "Risk management", "Attribution", "Systematic investing", "Financial markets", "Execution trading", "Quantitative investment" ], "skillCount" : 24, "jobCategory" : "other", "jobSubcategory" : "ceqr", "dataQualityScore" : 0.8888889, "_score" : 783.3566, "daysOld" : 2, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Financial Services" }, { "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" : 778.7506, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Financial Services" }, { "id" : "69cf3f042beec4dd3d93404b", "title" : "Sr. Quantitative UX Researcher, Applied AI Solutions", "company" : "Amazon Development Center U.S., Inc.", "industry" : "Design, Cloud Computing", "salary" : { "min" : 152200.0, "max" : 205900.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Seattle, Washington, USA", "locations" : [ "Seattle, Washington, USA" ], "timestamp" : "2026-06-15T03:38:33.708", "fingerprint" : "c75d0ccf14a6168cb656d3cee993a8ca37c2637c09d92ccd68c6286bab9a7f71", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/10382576/apply", "externalId" : "b8c61e57-b527-47f8-84a3-aa28a376c2fe", "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", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "SQL, Python, R, SAS, Matlab", "professionalSkills" : [ "Experimental design", "Quantitative analysis", "Insight generation", "Measurement strategies", "Behavioral analysis", "Causal inference", "Predictive intelligence", "Agentic AI products", "AI-Native Research Innovation", "Data Synthesis", "Executive Storytelling", "Engagement metrics", "Experiment data", "User logs", "AI performance metrics", "Product improvements", "Business strategy", "Build test learn", "Cross-Org Research Standards", "Research frameworks", "Measurement criteria", "Reusable methodologies" ], "hardSkillsList" : [ "Quantitative approaches", "Behavioral data collection", "Quantitative data analysis", "Statistics" ], "hardSkills" : [ { "name" : "Quantitative approaches", "level" : "intermediate" }, { "name" : "Behavioral data collection", "level" : "intermediate" }, { "name" : "Quantitative data analysis", "level" : "intermediate" }, { "name" : "Statistics", "level" : "intermediate" } ], "majorSkills" : "Quantitative UX Research, Applied AI, Experimentation, Causal inference", "majorSkillsList" : [ "Quantitative UX Research", "Applied AI", "Experimentation", "Causal inference" ], "coreResponsibilities" : "Lead quantitative research for AI products, Lead mixed-methods research for AI products, Lead research in 0 to 1 spaces, Own experimental design, Define hypotheses, Select research methods, Identify measures, Design studies, Analyze results, Translate findings into product actions, Pioneer AI-Native Research Innovation, Set industry standard for AI research, Invent methodologies for AI systems, Adapt methodologies for AI systems, Understand customer interaction with AI, Build trust in AI systems, Drive AI adoption, Triangulate research insights, Craft executive-ready narratives, Drive product improvements, Drive long-term business strategy, Partner with product, Partner with design, Partner with applied science, Partner with engineering, Support build test learn model, Use evidence to shape decisions, Establish Cross-Org Research Standards, Define research frameworks, Define measurement criteria, Define reusable methodologies, Create consistency in research, Raise research bar across AWS AI", "teamCollaboration" : "Partner closely with product; Partner closely with design; Partner closely with applied science; Partner closely with engineering", "domainKnowledge" : "AI-native business applications; Human-AI interaction; Agentic AI products", "domainList" : [ "ai-native-business-applications", "human-ai-interaction", "agentic-ai-products" ], "domainSpecificKnowledge" : [ "AI-native business applications", "Human-AI interaction", "Agentic AI products" ], "communicationSkills" : "Executive Storytelling", "innovationCreativity" : "AI-Native Research Innovation; Invent AI-enabled tools; Invent AI-enabled frameworks; Invent AI-enabled processes", "problemSolvingSkills" : "Turning ambiguous questions into hypotheses; Turning hypotheses into metrics; Turning metrics into studies; Turning studies into evidence", "outcomesObjectives" : "Define success for new agentic AI products; Create new ways to measure experiences; Define success metrics for agentic AI products; Identify behavioral signals; Identify attitudinal signals; Drive optimizations based on data; Improve how teams learn internally; Scale research impact across organization", "qualificationsBasic" : "Portfolio demonstrating past work, 5+ years leading User Research projects, Knowledge of quantitative approaches, 8+ years data querying languages, 8+ years scripting languages, 8+ years statistical/mathematical software, Experience working with AI systems, Experience with behavioral data collection, Experience with quantitative data analysis, Experience with statistics, Master's degree or equivalent in quantitative field", "qualificationsPreferred" : "Experience creating processes, Experience improving tools, Experience with innovation, Experience with development, Experience with testing, Experience communicating with senior leadership, Experience building machine learning models, Doctorate/PhD or equivalent", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "We're seeking a Sr. Quantitative UX Researcher who is passionate about shaping the future of AI-native business applications at scale. This is a rare opportunity to define the research strategy for one of Amazon's next generation of AI-powered solutions — influencing not just product direction, but the broader field of human-AI interaction. As a Sr. Quantitative UX Researcher, you will own experimental design, quantitative analysis, insight generation, and the measurement strategies that turn AI capabilities into meaningful, trustworthy, and human-centered experiences for millions of customers worldwide. You will help teams build, test, and learn faster by turning ambiguous product questions into clear hypotheses, meaningful success metrics, rigorous studies, and decision-ready evidence. Your work will be instrumental to how we evaluate early ideas, improve production experiences, and decide where to invest next. This is a quant-first role, with mixed-methods responsibilities as needed. We are looking for a researcher with deep expertise in experimentation, analytics, behavioral analysis, causal inference, and predictive intelligence. You will work in 0 to 1 environments, define success for new agentic AI products, and create new ways to measure experiences that do not yet have established playbooks. You will define success metrics for agentic AI products, identify the behavioral and attitudinal signals that matter most, and drive optimizations based on what the data shows. You will also invent AI-enabled tools, frameworks, and processes that improve how teams learn internally and scale research impact across the organization. Key job responsibilities - Lead quantitative and mixed-methods research for new and emerging AI products, especially in 0 to 1 spaces where customer needs, product behaviors, and success criteria are still being defined. - Own experimental design from end to end. This includes defining hypotheses, selecting methods, identifying measures, designing studies, analyzing results, and translating findings into clear product actions. - Pioneer AI-Native Research Innovation: Set the industry standard for AI-focused user research by inventing and adapting methodologies to understand how customers interact with AI systems, building trust, and driving adoption at scale - Data Synthesis and Executive Storytelling: Triangulate research insights with engagement metrics, experiment data, user logs, and AI performance metrics to craft compelling, executive-ready narratives that drive product improvements and long-term business strategy - Partner closely with product, design, applied science, and engineering to support a build, test, learn model of development, where evidence is used early and often to shape decisions. - Establish Cross-Org Research Standards: Define and institutionalize research frameworks, measurement criteria, and reusable methodologies that create consistency and raise the bar across all AI solutions and teams within AWS 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 business outcomes. Basic Qualifications: - Have a portfolio demonstrating past work experience and deliverables (e.g., study plans, reports, personas) - 5+ years of proven success leading User Research projects with demonstrated impact experience - Knowledge of quantitative approaches (e.g., t-tests, regressions, ANOVAs, etc.) - 8+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience - Experience working with or evaluating AI systems - Experience with behavioral data collection, quantitative data analysis, and statistics - Master's degree or equivalent in a quantitative field, or Doctorate/PhD or equivalent Preferred Qualifications: - Experience creating processes and improving tools that have measurably improved productivity, quality, or advertiser experience - Experience with innovation, development, testing - Experience communicating effectively with senior leadership - Experience in building machine learning models for business application 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 - 167,400.00 - 226,500.00 USD annually USA, WA, Seattle - 152,200.00 - 205,900.00 USD annually", "summaryDescription" : "Sr. Quantitative UX Researcher, Applied AI Solutions at Amazon Development Center U.S., Inc.. Skills: Quantitative UX Research, Applied AI, Experimentation, Causal inference. Lead quantitative research for AI products. Lead mixed-methods research for AI products", "postedDate" : "2026-06-13T02:19:14.551", "createdAt" : "2026-06-13T02:19:14.551", "lastUpdated" : "2026-06-15T03:38:33.708", "ingestTimestamp" : "2026-06-13T02:19:14.551", "mongoId" : "69cf3f042beec4dd3d93404b", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/10382576/apply", "salaryAnnualMin" : 152200, "salaryAnnualMax" : 205900, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Quantitative approaches", "Behavioral data collection", "Quantitative data analysis", "Statistics", "Quantitative UX Research", "Applied AI", "Experimentation", "Causal inference", "Experimental design", "Quantitative analysis", "Insight generation", "Measurement strategies", "Behavioral analysis", "Predictive intelligence", "Agentic AI products", "AI-Native Research Innovation", "Data Synthesis", "Executive Storytelling", "Engagement metrics", "Experiment data", "User logs", "AI performance metrics", "Product improvements", "Business strategy", "Build test learn", "Cross-Org Research Standards", "Research frameworks", "Measurement criteria", "Reusable methodologies", "AI-native business applications", "Human-AI interaction" ], "skillCount" : 31, "jobCategory" : "design", "dataQualityScore" : 1.0, "_score" : 758.6486, "daysOld" : 2, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology" }, { "id" : "6a2db57d74d8ee00a0c924a7", "title" : "Trade Marketing Specialist", "company" : "Stanley Black & Decker", "industry" : "Manufacturing", "salary" : { "min" : 750000.0, "max" : 1100000.0, "currency" : "CZK", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-level Trade Marketing Specialist in Prague, Czech Republic, adjusted for the manufacturing industry and company size." }, "location" : "Prague, Czechia", "locations" : [ "Prague, Czechia" ], "timestamp" : "2026-06-15T21:25:50.335", "fingerprint" : "570ee43a915b3925fb38cc5a9b9bbb7aeb78d87ed1958ecf9117f561b3547c2f", "source" : "workday", "language" : "en", "applyUrl" : "https://sbdinc.wd1.myworkdayjobs.com/Stanley_Black_Decker_Career_Site/job/Prague-Czechia/Trade-Marketing-Specialist_REQ-1000049133", "externalId" : "REQ-1000049133", "industryFunction" : { }, "locationPoint" : "50.08804,14.42076", "structuredLocations" : [ { "city" : "Prague", "country" : "Czech Republic", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "50.0874654,14.4212535" } ], "locationText" : "Prague, Czech Republic", "employmentType" : "FULL_TIME", "professionalSkills" : [ "Promotional strategy", "Marketing plans", "Pricing policy", "Budget management", "Market analyses", "Sales activities" ], "hardSkillsList" : [ "Campaign performance reporting", "ROI analysis" ], "hardSkills" : [ { "name" : "Campaign performance reporting", "level" : "intermediate" }, { "name" : "ROI analysis", "level" : "intermediate" } ], "majorSkills" : "Trade Marketing, Promotional Strategy, Campaign Management, Budget Management", "majorSkillsList" : [ "Trade Marketing", "Promotional Strategy", "Campaign Management", "Budget Management" ], "coreResponsibilities" : "Implement promotional strategy, Develop marketing plans, Introduce promotions and products, Create pricing policy, Develop price lists, Implement price lists, Organize events, Organize catalogues, Organize fairs, Manage translations, Adapt marketing for local market, Create local sell activities, Cooperate with local sales teams, Translate materials, Adapt materials, Work with translation agency, Manage budget, Process purchase orders, Allocate funds for ROI, Measure marketing campaign performance, Report marketing campaign performance, Gain marketing insights, Assess marketing goals, Monitor competition activities, Conduct market analyses, Analyze market for new channels, Analyze market for new customers, Analyze market for new partners, Conduct customer meetings, Conduct customer visits, Update systems, Set up pricing", "teamCollaboration" : "Cooperation with Marketing Manager; Cooperation with CE digital manager; Cooperation with social media manager; Cooperation with CE marketing team; Cooperation with CEE region; Cooperation with sales team", "domainKnowledge" : "CZ/SK market", "domainList" : [ "cz-sk-market" ], "domainSpecificKnowledge" : [ "CZ/SK market" ], "outcomesObjectives" : "Achieve best ROI", "qualificationsBasic" : "5+ years marketing experience, Experience with pricing policy, Experience with budget management, Experience with PO process, Experience with market analyses, Experience with system updates, Experience with pricing setup", "qualificationsPreferred" : "Experience in CZ/SK market", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "* * Setting and implementing promotional strategy, long and short-term marketing plans * Introducing promotions, new products, concepts, displays, etc. * Creation of pricing policy according to company guidelines, pricing process and price lists development and implementation in CZ/SK * Organizing events, catalogues, fairs, translations * Very close cooperation with Marketing Manager Stanley and implementation and adaptation for local market * Creation and execution of local sell activities and cooperation with local sales teams * Translation and adaptation of materials and work with translation agency * Close cooperation with CE digital and social media manager * Budget management including purchase orders process (PO) and allocate/invest funds to achieve best ROI for CZ/SK budget * Measure and report performance of marketing campaigns, gain insight and assess against goals * Competition activities monitoring, market analyses * Close cooperation with sales team in CZ/SK * Regular contact with CE marketing team members and also CEE region * Administrate various tasks – system updates, pricing set up, … * Analyze the market and competition to identify new channels, customers, partners * Regular customer meetings and visits ** _We Don’t Just Build The World, We Build Innovative Technology Too._** Joining the Stanley Black & Decker team means working in an innovative, tech-driven and highly collaborative team environment supported by over 43,500 professionals in 60 countries across the globe. Here, you’ll get the unique chance to impact some of the world’s most iconic brands including STANLEY TOOLS, DEWALT, CRAFTSMAN, MAC TOOLS and Black + Decker. Your ideas and solutions have the potential to reach millions of customers as we work together to write the next chapter in our history. Come build with us and take your career to new heights. **Who We Are** We’re the World’s largest tool company. We’re industry visionaries. We’re solving problems and advancing the manufacturing trade through innovative technology and our Industry 4.0 Initiative. We are committed to ensuring our state-of-the-art “smart factory” products and services provide greater quality to our customers & greater environmental and social value to our planet. We are unique in that we have a rich and storied history dating back to 1843, but that hasn't stopped us from evolving into a vibrant, diverse, global growth company. **Global Benefits & Perks** You’ll be rewarded with a competitive salary plus receive entitlements and benefits unique to your country of hire. **What You’ll Also Get** Career Opportunity: Career paths aren’t linear here. Being part of our global company with 60+ brands gives you the chance to grow and develop your skills along multiple career paths. **Learning & Development: ** Our lifelong learning philosophy means you’ll have access to a wealth of state-of-the-art learning resources, including our Lean Academy and online university (where you can get certificates and specializations from renowned colleges and universities). **Diverse & Inclusive Culture:** We pride ourselves on being an awesome place to work. We respect and embrace differences because that’s how the best work gets done. You’ll find we like to have fun here, too. **Purpose-Driven Company:** You’ll help us continue to make positive changes in the local communities where we work and live as well as in the broader world through volunteerism, giving back and sustainable business practices.", "summaryDescription" : "Trade Marketing Specialist at Stanley Black & Decker. Skills: Trade Marketing, Promotional Strategy, Campaign Management, Budget Management. Implement promotional strategy. Develop marketing plans", "postedDate" : "2026-06-13T20:51:52.893", "createdAt" : "2026-06-14T20:51:52.844", "lastUpdated" : "2026-06-15T21:25:50.335", "ingestTimestamp" : "2026-06-14T20:51:52.844", "mongoId" : "6a2db57d74d8ee00a0c924a7", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://sbdinc.wd1.myworkdayjobs.com/Stanley_Black_Decker_Career_Site/job/Prague-Czechia/Trade-Marketing-Specialist_REQ-1000049133", "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Campaign performance reporting", "ROI analysis", "Trade Marketing", "Promotional Strategy", "Campaign Management", "Budget Management", "Promotional strategy", "Marketing plans", "Pricing policy", "Budget management", "Market analyses", "Sales activities", "CZ/SK market" ], "skillCount" : 13, "jobCategory" : "marketing", "jobSubcategory" : "growth", "seniorityLevel" : "mid", "dataQualityScore" : 0.8888889, "_score" : 754.9295, "daysOld" : 2, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Manufacturing", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6d1374d8ee00a091d0a9", "title" : "Experienced Alpha Research Scientist", "company" : "Edgestream", "industry" : "FinTech", "salary" : { "min" : 220000.0, "max" : 320000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Alpha Research Scientist in Princeton, United States, adjusted for FinTech industry and company size." }, "location" : "Princeton, New Jersey, United States", "locations" : [ "Princeton", "New Jersey", "United States" ], "timestamp" : "2026-06-16T02:46:00.385", "fingerprint" : "ad57b18c60871af270bf2a5ffd1e587329ec9938d4c92e9bec4eddd108d9b2f4", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://www.edgestreamlp.com/career?gh_jid=4625706003", "externalId" : "4625706003", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Princeton", "state" : "New Jersey", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.3496953,-74.6597376" } ], "locationText" : "Princeton, New Jersey, United States", "minimumEducation" : "PhD", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, SQL", "professionalSkills" : [ "Quantitative analysis", "Scientific research", "Analytical abilities", "Mathematical abilities" ], "hardSkillsList" : [ "Statistical analysis", "Machine learning", "Algorithm development", "Data modelling" ], "hardSkills" : [ { "name" : "Statistical analysis", "level" : "intermediate" }, { "name" : "Machine learning", "level" : "intermediate" }, { "name" : "Algorithm development", "level" : "intermediate" }, { "name" : "Data modelling", "level" : "intermediate" } ], "majorSkills" : "Quantitative modeling, Financial markets, Machine learning", "majorSkillsList" : [ "Quantitative modeling", "Financial markets", "Machine learning" ], "coreResponsibilities" : "Develop quantitative models, Trade systematically, Conduct basic research, Investigate new datasets, Build research platform, Implement trading systems, Analyze live trading systems", "teamCollaboration" : "Work together; Cooperate and share ideas", "domainKnowledge" : "Financial markets; Statistics; Information theory; Algorithms", "domainList" : [ "financial-markets", "statistics", "information-theory", "algorithms" ], "domainSpecificKnowledge" : [ "Financial markets", "Statistics", "Information theory", "Algorithms" ], "innovationCreativity" : "Creativity", "problemSolvingSkills" : "Analytical abilities; Mathematical abilities", "qualificationsBasic" : "PhD or equivalent experience, Track record of high achievement, Comfort with large data, Comfort with programming", "qualificationsPreferred" : "PhD in scientific or engineering discipline", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Job Title: Experienced Alpha Research Scientist Edgestream Partners is a tight-knit team of scientists, engineers, and business professionals who devote our talents to developing quantitative models of financial markets and using them to trade systematically around the world and around the clock. Edgestream’s culture has more in common with research laboratories and technology startups than with traditional finance. We prize curiosity, creativity, diligence, and intellectual honesty. We focus on the long term, working together to build elegant and general systems that endure and scale as we grow. And we incentivize our employees to cooperate and share ideas, because we know that compounding our efforts magnifies our achievements. The result is a company where smart, dedicated effort can have a major impact. We’ve been in the business of managing hedge funds since 2003, and we’re still growing. We’re looking for talented, curious, and driven people who can grow with us in the years ahead. About the Job The Research group at Edgestream consists of highly skilled scientists and engineers, working in collaboration to unravel some of the finance’s hardest problems. Our ranks include physicists, mathematicians, biologists, machine learning experts, cryptographers, and theoretical computer scientists. We are responsible for the creation of the scientific models of market behavior which drive trading in our funds. Our investment process is fully research driven, and new members of our team quickly find that they have the opportunity to contribute directly to the company’s bottom line. Our work covers the full spectrum from basic research in statistics, information theory, and algorithms, to investigating new datasets, to building out our research platform, to implementation and analysis of live trading systems. This position will be located in either Princeton, NJ or New York, NY. Qualifications: PhD in a scientific or engineering discipline (or equivalent experience). Track record of high achievement in scientific research. Strong analytical and mathematical abilities. Comfort with large data and programming. No knowledge of finance is required. Some of the benefits of working at Edgestream: Competitive salary, bonus, and incentive compensation based on overall company performance. Fantastic resources, accumulated over decades, for turning ideas into reality. Comprehensive, first-class benefits (including excellent medical and dental insurance, 401(k), HRA, FSA, life insurance, daily catered lunch, and an onsite gym). For qualified employees, the opportunity to invest in our funds. Contact Info E-mail: careers@edgestreamlp.com. Legal disclaimer: In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification document form upon hire.", "summaryDescription" : "Experienced Alpha Research Scientist at Edgestream. Skills: Quantitative modeling, Financial markets, Machine learning. Develop quantitative models. Trade systematically", "postedDate" : "2026-06-14T18:58:59.292", "createdAt" : "2026-06-14T18:58:59.292", "lastUpdated" : "2026-06-16T02:46:00.385", "ingestTimestamp" : "2026-06-14T18:58:59.292", "mongoId" : "6a2c6d1374d8ee00a091d0a9", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 220000, "salaryAnnualMax" : 320000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Statistical analysis", "Machine learning", "Algorithm development", "Data modelling", "Quantitative modeling", "Financial markets", "Quantitative analysis", "Scientific research", "Analytical abilities", "Mathematical abilities", "Statistics", "Information theory", "Algorithms" ], "skillCount" : 13, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "_score" : 747.75476, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "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" : 742.9096, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.98 } ], "status" : 200, "message" : "OK", "pagination" : { "page" : 0, "limit" : 50, "totalCount" : 20589, "totalPages" : 412, "hasNext" : true, "hasPrevious" : false } }

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