{ "count" : 22991, "data" : [ { "id" : "6a305a2af292fd229cf4dcbf", "title" : "26-27 South Campus Boys & Girls Track and Field Head Coach", "industry" : "Sports & Fitness", "salary" : { "min" : 45000.0, "max" : 75000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Head Coach in Milwaukee, adjusted for lead seniority in the education industry." }, "location" : "Milwaukee, WI", "locations" : [ "Milwaukee, WI" ], "timestamp" : "2026-06-16T05:08:08.528", "fingerprint" : "2968d03627b56c1903b6bbeafdfcc0c5dc08c852d13ea105a6ca867adfaf3119", "source" : "jazzhr", "language" : "en", "externalId" : "vxUGbuv0EQ", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Milwaukee", "state" : "Wisconsin", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "43.0386475,-87.9090751" } ], "locationText" : "Milwaukee, Wisconsin, United States", "majorSkills" : "Track and Field", "majorSkillsList" : [ "Track and Field" ], "coreResponsibilities" : "Coach boys and girls track and field", "domainKnowledge" : "Track and Field", "domainList" : [ "track-and-field" ], "domainSpecificKnowledge" : [ "Track and Field" ], "qualificationsBasic" : "Head Coach experience", "workSiteFlexibility" : "Onsite", "summaryDescription" : "26-27 South Campus Boys & Girls Track and Field Head Coach. 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Coach boys and girls track and field", "createdAt" : "2026-06-15T22:24:48.709", "lastUpdated" : "2026-06-16T05:08:08.528", "ingestTimestamp" : "2026-06-15T22:24:48.709", "mongoId" : "6a305a2af292fd229cf4dcbf", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 45000, "salaryAnnualMax" : 75000, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Track and Field" ], "skillCount" : 1, "jobCategory" : "general", "jobSubcategory" : "general", "seniorityLevel" : "Lead", "dataQualityScore" : 0.44444445, "_score" : 624.70593, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Education", "llmIndustryConfidence" : 0.85 }, { "id" : "6a2c923574d8ee00a09852be", "title" : "Error Resolution", "company" : "SanMar", "industry" : "Retail", "salary" : { "min" : 19.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Avondale, AZ", "locations" : [ "Avondale", "AZ" ], "certifications" : [ "SanMar’s Lift Operator Certification" ], "timestamp" : "2026-06-15T13:53:50.398", "fingerprint" : "584dbc8353f308275dcd84ad693321f0331424df4a31544dc2c1800953a82156", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://boards.greenhouse.io/sanmar/jobs/5164013007?gh_jid=5164013007", "externalId" : "5164013007", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Avondale", "state" : "Arizona", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "33.4355977,-112.3496020" } ], "locationText" : "Avondale, Arizona, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "High School", "hardSkillsList" : [ "Operate powered equipment", "Lift operation" ], "hardSkills" : [ { "name" : "Operate powered equipment", "level" : "intermediate" }, { "name" : "Lift operation", "level" : "intermediate" } ], "majorSkills" : "Error resolution, Inventory management, Order fulfillment", "majorSkillsList" : [ "Error resolution", "Inventory management", "Order fulfillment" ], "coreResponsibilities" : "Identify and troubleshoot discrepancies, Adjust inventory quantities, Maintain accurate department records, Process ship short orders, Identify, correct, and record mill errors, Review customer orders prior to shipping, Operate powered lift equipment", "teamCollaboration" : "Work within a team", "domainKnowledge" : "Warehouse operations", "domainList" : [ "warehouse-operations" ], "domainSpecificKnowledge" : [ "Warehouse operations" ], "communicationSkills" : "Verbal communication; Written communication", "problemSolvingSkills" : "Problem-solving; Troubleshoot discrepancies", "specialRequirements" : "Operate powered equipment, Lift up to 60 pounds, Full range of motion, Repetitive hand motions, Climb stairs, Kneel/squat, Bend and carry, Wear Personal Protective Equipment, Work near conveyor systems, Exposure to dust, Exposure to extreme heat, Exposure to extreme cold, Work in hectic environment, Work in fast-paced environment", "outcomesObjectives" : "Complete and ship customer orders; Meet deadlines", "qualificationsBasic" : "High School Diploma or equivalent, Basic English literacy", "qualificationsPreferred" : "1-3 years warehouse experience, SanMar's Lift Operator Certification", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "At SanMar, the work you do makes a difference. Shift: 12:30PM-9:00PM Pay: $18.00 + $1.00 Shift Differential = $19.00 What's the Short Version? The Error Resolution role researches and resolves any discrepancies with shipments, locations, or product. They are responsible for quickly and accurately locating missing product to complete and ship customer orders in a timely fashion. What Will You Be Doing? • Identify and troubleshoot discrepancies with shipments, inventory and orders and adjust inventory quantities. • Maintain accurate department records. • Understand and accurately processes ship short orders. • Properly identify, correct, and record mill errors. • Review selected customer orders prior to shipping. • May be required to operate powered lift equipment. What Are We Looking For? • High School Diploma or equivalent • 1-3 years of warehouse experience is preferred • Ability to read, write and have sufficient ability to identify colors, sizes, quantity, label and SKU information • Ability to work with and keep a positive, supportive attitude towards the Company, job, customers and co-workers • May be required to complete and maintain SanMar’s Lift Operator Certification in compliance with OSHA recommendation • Demonstrates ability to follow directions and change priorities or job duties as business needs require • Excellent problem-solving skills • Demonstrated verbal and written communication skills • Strong attention to detail • Ability to work in high demand, high volume environment and meet deadlines • Must have exemplary performance in regard to attendance, accuracy and productivity • Excellent organization skills; demonstrating the ability to multi-task and prioritize daily responsibilities • Comprehends verbal and written instructions • Able to work both independently and within a team • Essential days or overtime may be required What's Our Offer? Paid Time Off: You`ll accrue paid time off on a weekly basis based on hours worked up to 112 hours per year to start. Employees also receive 8 paid holidays and 1 paid family day off. Additional Benefits: • Comprehensive medical, dental, and vision benefits • 401k plan and matches $1 for $1 up to 4% of earnings, matched & vested at every pay cycle • Life insurance • Short/long-term disability coverage • Paid maternity/paternity leave • Pet insurance What Should You Expect? DC Warehouse (Equipment): While performing the duties of this job, the employee is constantly required to stand, walk, talk and hear. The employee frequently lifts and/or moves up to 60 pounds. The employee operates powered equipment requiring use of both hands as well as full range of motion of the neck, head and back. The employee is frequently required to reach with hands and arms, grasp and perform repetitive hand, wrist and arm motions. The employee is frequently required to climb stairs, kneel/squat, bend and carry. Specific vision abilities required by this job include close vision, color vision, peripheral vision, depth perception and ability to adjust focus. Employee may be required to wear a headset covering one or both ears. Employee will be required to wear Personal Protective Equipment such as a protective harness while operating equipment. Basic English literacy is required for operation of machines and necessary daily paperwork. Work environment is moderately noisy. The employee is occasionally required to work near conveyor systems. There is exposure to dust and changes in weather conditions. Work is performed under typical warehouse conditions. Potential hazards exist with regard to machinery such as forklifts, pallet jacks, mechanized systems, etc. Work environment is hectic and fast-paced. The employee is regularly exposed to ambient lighting and can be exposed to extreme heat and extreme cold including climates consistent with outside weather conditions. Why Work at SanMar? Our people are at the heart of everything we do. They bring their talent, passion and dedication to work with them every day. Their hard work inspires us and gives us purpose. We love working here together. Whether you work in our headquarters, from your home or in one of our distribution centers across North America, we believe that investing in you is just the right thing to do. Our comprehensive benefits package is designed to support your health and well-being, life balance, career growth and (eventually) retirement. SanMar works with brands you already know, like Nike, The North Face and Brooks Brothers, as well as providing industry-leading private label apparel and accessories. Our people come to work excited to do their part, providing clothing that helps people feel that they’re a part of something special. Here’s your chance to be a part of this story. If you’re ready to work in a place where your participation matters and your growth is a priority, we’re ready for you. SanMar is an Equal Opportunity Employer Whoever you are, wherever you’re from, whoever you love or follow in faith, whatever your disability or superpower status, whichever ethnicity or gender you identify with, you are welcome at SanMar. SanMar participates in E-Verify.", "summaryDescription" : "Error Resolution at SanMar. Skills: Error resolution, Inventory management, Order fulfillment. Identify and troubleshoot discrepancies. Adjust inventory quantities", "postedDate" : "2026-06-14T05:56:12.832", "createdAt" : "2026-06-14T05:56:12.832", "lastUpdated" : "2026-06-15T13:53:50.398", "ingestTimestamp" : "2026-06-14T05:56:12.832", "mongoId" : "6a2c923574d8ee00a09852be", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 39520, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Operate powered equipment", "Lift operation", "Error resolution", "Inventory management", "Order fulfillment", "Warehouse operations", "SanMar’s Lift Operator Certification" ], "skillCount" : 7, "jobCategory" : "operations", "jobSubcategory" : "general", "seniorityLevel" : "Junior", "dataQualityScore" : 0.8888889, "_score" : 606.4178, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Logistics", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2ca43874d8ee00a09b0c0a", "title" : "Fast Track to Leadership Trainee", "company" : "Picnic", "industry" : "Logistics", "salary" : { "min" : 45000.0, "max" : 55000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for entry-level e-commerce roles in Germany, adjusted for the specific company and city tier." }, "location" : "Germany ", "locations" : [ "Germany" ], "timestamp" : "2026-06-16T01:07:42.722", "fingerprint" : "021c96bde1cc2ac719cc68879b0f8a9a32e2bfb3d52d591182a94e60b4615b6c", "source" : "greenhouse", "language" : "de", "applyUrl" : "https://jobs.picnic.app/nl/vacancies?gh_jid=7730888", "externalId" : "7730888", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Germany", "continent" : "eu", "workMode" : "onsite" } ], "locationText" : "Germany", "employmentType" : "FULL_TIME", "minimumEducation" : "Master's", "experienceMinYears" : 0, "experienceMaxYears" : 2, "experienceLevel" : "Entry", "professionalSkills" : [ "Process management", "Resource planning", "Continuous improvement" ], "hardSkillsList" : [ "Operational decision making", "Process optimization", "Data analysis" ], "softSkillsList" : [ "Leadership", "Mentoring", "Motivation", "Coaching" ], "hardSkills" : [ { "name" : "Operational decision making", "level" : "intermediate" }, { "name" : "Process optimization", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" }, { "name" : "Motivation" }, { "name" : "Coaching" } ], "majorSkills" : "Supply Chain Management, Operations Management, Team Leadership", "majorSkillsList" : [ "Supply Chain Management", "Operations Management", "Team Leadership" ], "coreResponsibilities" : "Plan shifts, Coordinate shifts, Lead shifts, Develop people, Create clarity, Master challenging situations, Identify optimization potential, Implement improvement projects, Increase productivity, Simplify processes, Solve bottlenecks, Take responsibility for new environment, Support new FCs, Optimize ordering processes, Support automated FCs", "teamCollaboration" : "Cross-functional teams; International teams", "projectManagementSkills" : [ "Project implementation", "Improvement projects" ], "domainKnowledge" : "Supply Chain; Fulfillment Center Operations; Logistics", "domainList" : [ "supply-chain", "fulfillment-center-operations", "logistics" ], "domainSpecificKnowledge" : [ "Supply Chain", "Fulfillment Center Operations", "Logistics" ], "continuousLearning" : "Internal learning opportunities; Workshops; Bootcamps", "innovationCreativity" : "Test new ideas", "problemSolvingSkills" : "Identify problems; Solve problems", "specialRequirements" : "Shift work, Office and warehouse environment", "outcomesObjectives" : "Increase productivity; Simplify processes; Solve bottlenecks; Elevate supply chain", "qualificationsBasic" : "Master's degree in Logistics, Master's degree in Supply Chain Management, Master's degree in Industrial Engineering, Master's degree in comparable field, First practical experience in supply chain, Fluent German, Very good English skills", "qualificationsPreferred" : "Experience in operations supervisor role, Experience in operations manager role", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "Kurz und knapp Du stehst kurz vor deinem Masterabschluss und willst als Graduate mehr als nur einen klassischen Berufseinstieg? Du suchst Verantwortung, Tempo und echte Wirkung in deinem Alltag? Als Fast Track to Leadership Trainee im Bereich Supply Chain und Operations startest du bei Picnic durch: In nur zwei Jahren entwickelst du dich vom Graduate in die Führungsposition als Operations Manager und übernimmst die Verantwortung für Teams, Prozesse und strategische Projekte entlang unserer Supply Chain im Fulfillment. Hands-on, datengetrieben und mit echtem Impact. Das erwartet dich Jahr 1: Operative Grundlagen & Leadership als Operations Supervisor Onboarding & Einstieg: Du startest mit einem strukturierten Onboarding, baust dir ein starkes Netzwerk auf und lernst unser Fulfillment Center (FC) von Grund auf kennen. Schichtleitung im FC: An ca. 3-4 Tagen pro Woche übernimmst du als Operations Supervisor die Verantwortung einer Schicht. Du planst, koordinierst und führst dein Team - und erlebst vom ersten Tag an, wie operative Entscheidungen direkten Einfluss auf unsere Teams und Performance haben. Führung & Coaching: Durch Mentoring, Trainings zu Leadership, Feedback und Motivation lernst du, wie du Menschen entwickelst, Klarheit schaffst und herausfordernde Situationen meisterst. Eigene Projekte mit Impact: Du identifizierst Optimierungspotenziale im operativen Alltag und setzt an deinen 1-2 Projekttagen eigenständig Verbesserungsprojekte um, die Produktivität steigern, Prozesse vereinfachen und Engpässe nachhaltig lösen. Jahr 2: Führung mit Wirkung über Standorte hinweg als Operations Manager (Inter)nationale Perspektive: Ergreife die Chance und bring dein Wissen an anderen Picnic Standorten - national oder international - oder lerne eine andere Abteilung entlang unserer Supply Chain kennen. Du übernimmst Verantwortung in einem neuen Umfeld mit neuen Teams und wächst über dich hinaus. Fokus auf Projekte: Neben deinen ca. 1-2 Schichttagen pro Woche arbeitest du an ca. 3-4 Tagen an standortübergreifenden Initiativen, z. B. bei der Optimierung unserer Bestellprozesse oder bei der Unterstützung neuer (automatisierter) FCs. Mit deinem operativen Know-How und deinem analytischen Blick hebst du unsere Supply Chain auf das nächste Level. Dein nächster Schritt: Nach dem Fast Track stehen dir viele Türen offen: als erfahrener Operations Manager oder in weiteren Positionen innerhalb von Picnic. Das bringst du mit Ein (bald) abgeschlossenes Masterstudium in Logistik, Supply Chain Management, Wirtschaftsingenieurwesen oder einem vergleichbaren Masterstudiengang Erste praktische Erfahrungen im Supply-Chain-Umfeld (z. B. durch Praktika oder Werkstudententätigkeiten) Fließende Deutsch- und sehr gute Englischkenntnisse Freude daran, als Trainee direkt Verantwortung für ein Team zu übernehmen und Menschen zu motivieren und entwickeln Du setzt Ideen mit deiner Hands-on-Mentalität in erfolgreiche Projekte um und gehst als Vorbild voran Ein starkes Zahlenverständnis und die Fähigkeit, Probleme frühzeitig zu erkennen Flexibilität und Begeisterung für eine Rolle, die sowohl im Büro als auch im operativen Lagerumfeld stattfindet, inklusive Schichtarbeit Darauf kannst du dich freuen Starte durch - mit uns: Werde Teil unseres internationalen Teams in einem Umfeld, das echtes Wachstum und eine „Act like an Owner“-Mentalität fördert. Bei uns hast du die Chance, Projekte eigenverantwortlich voranzutreiben, neue Ideen zu testen und direkt miterleben zu können, wie deine Arbeit in unserem schnell wachsenden Unternehmen Wirkung zeigt. Nachhaltigkeit als Kern: Werde Teil der Revolution. Du trägst zu einer grüneren Zukunft bei – durch unsere 100 % elektrische Flotte und eine Lieferkette, die Lebensmittelverschwendung reduziert. Die Basics: Wir stellen dir alles für deinen Erfolg bereit – inklusive Laptop und Handy sowie Zugang zu exklusiven Mitarbeiter-Rabatten (Corporate Benefits) für Reisen, Technik und vieles mehr. Zeit zum Auftanken: Mit 30 Urlaubstagen pro Jahr (bei einer 40-Stunden-Woche) sorgst du für den perfekten Ausgleich zwischen Arbeit und Erholung. Verpflegung für Gewinner: Wir kümmern uns um dich. Genieße jeden Tag ein frisches, kostenloses Frühstück und Mittag- oder Abendessen in unserem Fulfilment Center, dazu gibt es reichlich Snacks, Getränke und Obst für den Energiekick zwischendurch. Unvergessliche Momente: Wir sind mehr als nur ein Team. Von unserem legendären jährlichen Ski-Trip über Weihnachtsfeiern bis hin zu Auftritten unserer eigenen Picnic-Band: Wir feiern unsere Erfolge gemeinsam. Wohlbefinden & Gleichgewicht: Wir bieten dir professionelle Unterstützung für deine mentale Gesundheit mit OpenUp. Individuelle Mobilität:Du erhältst einen Firmenwagen (auch zur privaten Nutzung) und kannst zusätzlich unser „Lease-a-Bike“-Programm nutzen. Lebensmittelretter: Hol dir unsere exklusiven \"Too-Good-To-Go\"-Tüten und rette leckere Lebensmittel – nur für unsere Mitarbeitenden! Lerne & wachse: Profitiere von internen Lern- & Entwicklungsmöglichkeiten durch spannende Workshops und intensive Bootcamps, um deine Skills ständig zu erweitern Bist du neugierig?", "summaryDescription" : "Fast Track to Leadership Trainee at Picnic. Skills: Supply Chain Management, Operations Management, Team Leadership. Plan shifts. Coordinate shifts", "postedDate" : "2026-06-14T21:36:50.105", "createdAt" : "2026-06-14T21:36:50.105", "lastUpdated" : "2026-06-16T01:07:42.722", "ingestTimestamp" : "2026-06-14T21:36:50.105", "mongoId" : "6a2ca43874d8ee00a09b0c0a", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "30k-50k", "hasSalary" : false, "allSkills" : [ "Operational decision making", "Process optimization", "Data analysis", "Leadership", "Mentoring", "Motivation", "Coaching", "Supply Chain Management", "Operations Management", "Team Leadership", "Process management", "Resource planning", "Continuous improvement", "Project implementation", "Improvement projects", "Supply Chain", "Fulfillment Center Operations", "Logistics" ], "skillCount" : 18, "jobCategory" : "operations", "jobSubcategory" : "general", "seniorityLevel" : "Entry", "dataQualityScore" : 1.0, "_score" : 586.83215, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "E-Commerce", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c75ec74d8ee00a09388a3", "title" : "Quantitative Developer", "company" : "Poesis", "industry" : "Engineering", "salary" : { "min" : 180000.0, "max" : 280000.0, "currency" : "USD", "frequency" : "Yearly" }, "location" : "San Francisco", "locations" : [ "San Francisco" ], "timestamp" : "2026-06-16T02:57:35.521", "fingerprint" : "3b2dc2fae32d1b45fec189e17e460b6008dc79f71883911d9bec5cf31a69d6a2", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/poesis/95065a70-aa63-4469-b98c-087201a28d77/application", "externalId" : "95065a70-aa63-4469-b98c-087201a28d77", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Menlo Park", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "37.4519671,-122.1779920" } ], "locationText" : "Menlo Park, California, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "technicalSkills" : "Python, Pandas, Numpy, Scipy, Matplotlib, SQL, Claude Code, Codex", "professionalSkills" : [ "Feature generation", "Back-testing", "Model evaluation", "Data schemas", "APIs", "Reproducibility standards" ], "hardSkillsList" : [ "Statistics", "Regression", "Optimization", "ML fundamentals" ], "softSkillsList" : [ "Clear communicator" ], "hardSkills" : [ { "name" : "Statistics", "level" : "intermediate" }, { "name" : "Regression", "level" : "intermediate" }, { "name" : "Optimization", "level" : "intermediate" }, { "name" : "ML fundamentals", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Clear communicator" } ], "majorSkills" : "Quantitative research, Model implementation, Data pipelines", "majorSkillsList" : [ "Quantitative research", "Model implementation", "Data pipelines" ], "coreResponsibilities" : "Implement and iterate on research ideas, Implement model prototypes, Clean financial datasets, Process financial datasets, Join financial datasets, Build processes for feature generation, Build processes for back-testing, Build processes for model evaluation, Maintain processes for feature generation, Maintain processes for back-testing, Maintain processes for model evaluation, Run experiments, Summarize results, Report findings to leadership, Contribute to code quality, Support defining data schemas, Support defining APIs, Support defining reproducibility standards, Implement models, Test models, Refine models, Implement signals, Test signals, Refine signals, Implement analytical workflows, Test analytical workflows, Refine analytical workflows, Maintain consistent cadence of deliverables, Focus on iteration speed, Focus on reliability", "teamCollaboration" : "Engineering leadership; Chief Scientist; CEO", "domainKnowledge" : "Financial datasets; Portfolio optimization; Risk modeling; Financial time-series", "domainList" : [ "financial-datasets", "portfolio-optimization", "risk-modeling", "financial-time-series" ], "domainSpecificKnowledge" : [ "Financial datasets", "Portfolio optimization", "Risk modeling", "Financial time-series" ], "toolProficiency" : [ "Git", "Docker", "Prefect", "Airflow" ], "communicationSkills" : "Explain technical findings", "documentationSkills" : "Documentation", "innovationCreativity" : "Research ideas; Model prototypes", "problemSolvingSkills" : "Analytical workflows", "specialRequirements" : "Work visa sponsorship", "qualificationsBasic" : "Python skills, SQL comfort, Claude Code, Codex, or other coding agents skill, Real-world financial datasets proficiency, Reproducible analyses or pipelines building, Statistics understanding, Regression understanding, Optimization understanding, ML fundamentals understanding, Clear communicator, BS/MS/PhD in Computer Science, Mathematics, Statistics, Physics, Finance or related quantitative field", "qualificationsPreferred" : "Prior full-time experience in finance, data science, or ML engineering, Early-stage startup experience, Demonstrated builder mindset", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "ABOUT POESIS Whoever builds the leading intelligence for finance will create far more than returns. Poesis is the AI-native investment firm running autonomous agents that predict markets, construct portfolios, and manage risk. Our founders managed institutional capital at Capital Group ($3T AUM) and led enterprise ML at Goldman Sachs and Amazon. We're building a new type of firm, where live capital is the training ground for an intelligence that compounds with every signal. ABOUT THE ROLE We’re hiring a Quantitative Developer to help turn research ideas into production-grade code. You’ll help build data pipelines, implement models and ensure results are clean, reproducible and explainable. You’ll work alongside Poesis’ Chief Scientist, CEO and engineering leadership to turn large-scale data and quantitative research into models, signals and tools that drive investment decision-making. RESPONSIBILITIES - Rapidly implement and iterate on research ideas and model prototypes. - Clean, process, and join financial and fundamental datasets from professional and public sources. - Build and maintain processes for feature generation, back-testing, and model evaluation. - Run experiments, summarize results, and report findings to leadership. - Contribute to code quality: testing, documentation, and integration into shared systems. - Support the team in defining data schemas, APIs, and reproducibility standards. - Implement, test, and refine models, signals, and analytical workflows. - Maintain a consistent cadence of deliverables, focusing on iteration speed and reliability. REQUIRED COMPETENCIES - Strong Python skills (pandas, numpy, scipy, matplotlib); comfort with SQL. - Skill working with Claude Code, Codex, or other coding agents. - Proficiency working with real-world financial datasets and building reproducible analyses or pipelines. - Understanding of statistics, regression, optimization, and ML fundamentals. - Clear communicator who can explain technical findings to non-specialists. - BS/MS/PhD in Computer Science, Mathematics, Statistics, Physics, Finance or related quantitative field. PREFERRED COMPETENCIES - Prior full-time experience in finance, data science, or ML engineering. - Familiarity with APIs from Bloomberg, CapIQ, FactSet, or Refinitiv. - Exposure to portfolio optimization, risk modeling, or financial time-series. - Skill with git, Docker, and modern orchestration tools (Prefect, Airflow, etc.). - Early-stage startup experience or demonstrated builder mindset. LOCATION Hybrid: 3 days per week on-site at our office in Menlo Park, CA. Relocation allowance available. BENEFITS We offer excellent medical, dental, and vision coverage, alongside a strong benefits package that includes catered lunches in our Menlo Park office, commuter benefits, and more. Current legal authorization to work in the US required; continuing work visa sponsorship available for full-time employees. WORKING AT POESIS As an early team member, you’ll help shape not just the product, but how the company operates. Your decisions will have lasting impact across the business. You’ll build from first principles, with no legacy systems, or entrenched processes slowing you down. Our team is made up of people from elite companies and universities who are low ego, collaborative, and excited to build together.", "summaryDescription" : "Quantitative Developer at Poesis. Skills: Quantitative research, Model implementation, Data pipelines. Implement and iterate on research ideas. Implement model prototypes", "createdAt" : "2026-06-14T18:38:40.209", "lastUpdated" : "2026-06-16T02:57:35.521", "ingestTimestamp" : "2026-06-14T18:38:40.209", "mongoId" : "6a2c75ec74d8ee00a09388a3", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 180000, "salaryAnnualMax" : 280000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Statistics", "Regression", "Optimization", "ML fundamentals", "Clear communicator", "Quantitative research", "Model implementation", "Data pipelines", "Feature generation", "Back-testing", "Model evaluation", "Data schemas", "APIs", "Reproducibility standards", "Financial datasets", "Portfolio optimization", "Risk modeling", "Financial time-series", "Git", "Docker", "Prefect", "Airflow" ], "skillCount" : 22, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Mid", "dataQualityScore" : 0.7777778, "_score" : 585.06775, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c68ca74d8ee00a0904c50", "title" : "Quantitative Developer", "company" : "TradingHub", "industry" : "Analytics & Data", "salary" : { "min" : 95000.0, "max" : 135000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-level Quantitative Developer in London, UK, adjusted for the FinTech industry." }, "location" : "London", "locations" : [ "London" ], "timestamp" : "2026-06-16T03:36:13.356", "fingerprint" : "a5891dc60db14cae01d4de338056b5787054ced27c5889ecbb74887ecd41b7d6", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/tradinghub/10a15c19-9c9e-4dda-b95c-e2936d618dea/application", "externalId" : "10a15c19-9c9e-4dda-b95c-e2936d618dea", "industryFunction" : { }, "structuredLocations" : [ { "city" : "London", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "hybrid", "geo" : "51.5074456,-0.1277653" } ], "locationText" : "London, United Kingdom", "employmentType" : "FULL_TIME", "technicalSkills" : "C#, C++, Python", "professionalSkills" : [ "Financial modeling", "Risk algorithms" ], "hardSkillsList" : [ "Mathematical skills", "Analytical skills" ], "hardSkills" : [ { "name" : "Mathematical skills", "level" : "intermediate" }, { "name" : "Analytical skills", "level" : "intermediate" } ], "majorSkills" : "Quantitative development, Pricing models, Financial markets", "majorSkillsList" : [ "Quantitative development", "Pricing models", "Financial markets" ], "coreResponsibilities" : "Design pricing models, Build pricing models, Validate pricing models, Create financial pricing libraries, Create calculators, Create risk algorithms, Develop financial pricing libraries, Develop calculators, Develop risk algorithms, Use in-house big data language, Perform large-scale analysis, Productionize securities data, Research market dynamics, Develop market dynamics, Prototype proprietary models, Test proprietary models, Validate proprietary models", "teamCollaboration" : "Fast-paced environment", "domainKnowledge" : "Financial markets; Multiple asset classes; Risk sensitivities; Greeks; Delta; Gamma; DV01; Derivatives; Swaps; Options; Futures", "domainList" : [ "financial-markets", "multiple-asset-classes", "risk-sensitivities", "greeks", "delta", "gamma", "dv01", "derivatives", "swaps", "options", "futures" ], "domainSpecificKnowledge" : [ "Financial markets", "Multiple asset classes", "Risk sensitivities", "Greeks", "Delta", "Gamma", "DV01", "Derivatives", "Swaps", "Options", "Futures" ], "toolProficiency" : [ "Big data language" ], "continuousLearning" : "Study leave", "innovationCreativity" : "Experiment with new ideas", "problemSolvingSkills" : "Analytical skills", "qualificationsBasic" : "Proficiency with C#, C++ or Python, Exceptional mathematical and analytical skills, Initial industry experience as quant, Knowledge of risk sensitivities, Understanding of derivatives", "qualificationsPreferred" : "Capacity to put yourself in eyes of trader", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "Compensation: Competitive (Financial Services) About TradingHub Founded in 2010, TradingHub delivers uniquely intelligent trade surveillance software to world leading financial institutions. Developed by market professionals, our solutions use sophisticated modelling techniques to detect single and cross-product market manipulation. With a team of over 150 experts worldwide, TradingHub combines global reach with deep markets expertise to help our customers mitigate financial, regulatory, and reputational risk. The Role We are seeking a Quantitative Developer to contribute in designing, building and validating our pricing models. This includes creating financial pricing libraries for multiple asset classes, calculators and risk algorithms. The successful candidate will combine excellent mathematical skills with proven experience in financial markets and the ability to productionise high-quality software. The capacity to put yourself in the eyes of a trader will be very useful as we continue to ensure our product’s capabilities are ahead of competitors in the market. Responsibilities: - Development of financial pricing libraries, calculators as well as risk/pricing-related algorithms - Using our in-house big data language for the large-scale analysis and production of securities data - Research and development of market dynamics across multiple asset classes - Prototyping, testing, and validation of TradingHub’s proprietary models Requirements - Proficiency with C#, C++ or Python - Evidence of exceptional mathematical and analytical skills - Initial industry experience working as a quant within a financial services organisation - Some knowledge of risk sensitivities or \"Greeks\" such as Delta, Gamma, DV01 etc. - Understanding of derivatives (e.g. swaps, options, futures) - Confidence to experiment with new ideas and technologies - Keen to work in a fast-paced environment Benefits Life at TradingHub is a rewarding journey within a fast-growing company that thrives on innovation and collaboration. By combining the best of technology and global markets, we’re able to solve complex problems together and deliver meaningful results to our customers. Everybody has value to bring, and we welcome individuality as a key driving force behind our collective success. Rooted in everything that we do are our core values: Accountability, Ambition, Partnership and Trust. These values provide the foundation for a sustainable workplace culture that empowers you to grow, contribute, and become your best self. Employee Benefits: - Annual discretionary performance bonus (permanent employees only) - Hybrid working policy - Office lunches twice a week - Private medical insurance + dental cover - Extended parental leave (up to 6 months of fully paid maternity leave) - 25 days annual leave + bank holidays - Enhanced company pension plan - 5 days study leave towards professional qualifications - Salary sacrifice schemes - Death in service coverage Don’t tick every single requirement? Research shows that candidates from under-represented groups are less likely to apply unless they meet all the criteria. We are dedicated to building a diverse, equitable and inclusive workplace, so if this role excites you, please don't let our specification hold you back. Get in touch! TradingHub is an equal opportunities employer. We do not discriminate based on race, religion, ethnic or national origins, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, socio-economic background, responsibilities for dependants, physical or mental disability or other applicable legally protected characteristics. TradingHub selects candidates for interview based solely on their skills, experience and qualifications. We are committed to making our recruitment process accessible to all and we encourage candidates to inform us of any required adjustments. A full copy of our diversity, equity and inclusion policy will be made available to you upon request.", "summaryDescription" : "Quantitative Developer at TradingHub. Skills: Quantitative development, Pricing models, Financial markets. Design pricing models. Build pricing models", "createdAt" : "2026-06-14T19:20:30.123", "lastUpdated" : "2026-06-16T03:36:13.356", "ingestTimestamp" : "2026-06-14T19:20:30.123", "mongoId" : "6a2c68ca74d8ee00a0904c50", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "75k-100k", "hasSalary" : false, "allSkills" : [ "Mathematical skills", "Analytical skills", "Quantitative development", "Pricing models", "Financial markets", "Financial modeling", "Risk algorithms", "Multiple asset classes", "Risk sensitivities", "Greeks", "Delta", "Gamma", "DV01", "Derivatives", "Swaps", "Options", "Futures", "Big data language" ], "skillCount" : 18, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Mid", "dataQualityScore" : 0.7777778, "_score" : 584.2423, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2ca43874d8ee00a09b0c0d", "title" : "Fast Track to Leadership Trainee", "company" : "Picnic", "industry" : "Logistics", "salary" : { "min" : 45000.0, "max" : 55000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an entry-level E-commerce trainee in Germany, adjusted for company size and industry." }, "location" : "Germany ", "locations" : [ "Germany" ], "timestamp" : "2026-06-15T21:59:18.600", "fingerprint" : "3b5c4e891d55a70b82119dbd67867fb685b0281cac681095949d896ec967b152", "source" : "greenhouse", "language" : "de", "applyUrl" : "https://jobs.picnic.app/nl/vacancies?gh_jid=7730885", "externalId" : "7730885", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Germany", "continent" : "eu", "workMode" : "onsite" } ], "locationText" : "Germany", "employmentType" : "FULL_TIME", "minimumEducation" : "Master's", "experienceMinYears" : 0, "experienceMaxYears" : 2, "experienceLevel" : "Entry", "professionalSkills" : [ "Supply chain management", "Operations management", "Process optimization", "Data analysis" ], "hardSkillsList" : [ "Process simplification", "Bottleneck resolution", "Order process optimization", "Team leadership", "People development" ], "softSkillsList" : [ "Leadership", "Mentoring", "Motivation", "Team development" ], "hardSkills" : [ { "name" : "Process simplification", "level" : "intermediate" }, { "name" : "Bottleneck resolution", "level" : "intermediate" }, { "name" : "Order process optimization", "level" : "intermediate" }, { "name" : "Team leadership", "level" : "intermediate" }, { "name" : "People development", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" }, { "name" : "Motivation" }, { "name" : "Team development" } ], "majorSkills" : "Operations Management, Team Leadership, Process Improvement", "majorSkillsList" : [ "Operations Management", "Team Leadership", "Process Improvement" ], "coreResponsibilities" : "Onboard and learn fulfillment center, Lead a shift in fulfillment center, Plan shift operations, Coordinate shift operations, Lead shift team, Identify optimization potential, Implement improvement projects, Take responsibility for teams, Take responsibility for processes, Take responsibility for strategic projects, Contribute to international perspective, Work on cross-site initiatives, Support new fulfillment centers, Optimize ordering processes, Support automated fulfillment centers", "teamCollaboration" : "Cross-functional teams; International teams", "projectManagementSkills" : [ "Project management" ], "domainKnowledge" : "Supply chain; Fulfillment center operations; Logistics; Food waste reduction", "domainList" : [ "supply-chain", "fulfillment-center-operations", "logistics", "food-waste-reduction" ], "domainSpecificKnowledge" : [ "Supply chain", "Fulfillment center operations", "Logistics", "Food waste reduction" ], "continuousLearning" : "Mentoring; Training; Workshops; Bootcamps; Learning opportunities", "innovationCreativity" : "Test new ideas", "problemSolvingSkills" : "Problem identification; Root cause analysis; Analytical thinking", "specialRequirements" : "Shift work, Office and warehouse environment, Company car, Private car use", "outcomesObjectives" : "Increase productivity; Simplify processes; Solve bottlenecks; Develop people; Create clarity; Master challenging situations; Grow beyond oneself; Elevate supply chain", "qualificationsBasic" : "Master's degree in Logistics, Master's degree in Supply Chain Management, Master's degree in Industrial Engineering, Master's degree in comparable field, Practical experience in supply chain, Fluent German, Very good English skills", "qualificationsPreferred" : "Experience through internships, Experience through working student roles", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "Kurz und knapp Du stehst kurz vor deinem Masterabschluss und willst als Graduate mehr als nur einen klassischen Berufseinstieg? Du suchst Verantwortung, Tempo und echte Wirkung in deinem Alltag? Als Fast Track to Leadership Trainee im Bereich Supply Chain und Operations startest du bei Picnic durch: In nur zwei Jahren entwickelst du dich vom Graduate in die Führungsposition als Operations Manager und übernimmst die Verantwortung für Teams, Prozesse und strategische Projekte entlang unserer Supply Chain im Fulfillment. Hands-on, datengetrieben und mit echtem Impact. Das erwartet dich Jahr 1: Operative Grundlagen & Leadership als Operations Supervisor Onboarding & Einstieg: Du startest mit einem strukturierten Onboarding, baust dir ein starkes Netzwerk auf und lernst unser Fulfillment Center (FC) von Grund auf kennen. Schichtleitung im FC: An ca. 3-4 Tagen pro Woche übernimmst du als Operations Supervisor die Verantwortung einer Schicht. Du planst, koordinierst und führst dein Team - und erlebst vom ersten Tag an, wie operative Entscheidungen direkten Einfluss auf unsere Teams und Performance haben. Führung & Coaching: Durch Mentoring, Trainings zu Leadership, Feedback und Motivation lernst du, wie du Menschen entwickelst, Klarheit schaffst und herausfordernde Situationen meisterst. Eigene Projekte mit Impact: Du identifizierst Optimierungspotenziale im operativen Alltag und setzt an deinen 1-2 Projekttagen eigenständig Verbesserungsprojekte um, die Produktivität steigern, Prozesse vereinfachen und Engpässe nachhaltig lösen. Jahr 2: Führung mit Wirkung über Standorte hinweg als Operations Manager (Inter)nationale Perspektive: Ergreife die Chance und bring dein Wissen an anderen Picnic Standorten - national oder international - oder lerne eine andere Abteilung entlang unserer Supply Chain kennen. Du übernimmst Verantwortung in einem neuen Umfeld mit neuen Teams und wächst über dich hinaus. Fokus auf Projekte: Neben deinen ca. 1-2 Schichttagen pro Woche arbeitest du an ca. 3-4 Tagen an standortübergreifenden Initiativen, z. B. bei der Optimierung unserer Bestellprozesse oder bei der Unterstützung neuer (automatisierter) FCs. Mit deinem operativen Know-How und deinem analytischen Blick hebst du unsere Supply Chain auf das nächste Level. Dein nächster Schritt: Nach dem Fast Track stehen dir viele Türen offen: als erfahrener Operations Manager oder in weiteren Positionen innerhalb von Picnic. Das bringst du mit Ein (bald) abgeschlossenes Masterstudium in Logistik, Supply Chain Management, Wirtschaftsingenieurwesen oder einem vergleichbaren Masterstudiengang Erste praktische Erfahrungen im Supply-Chain-Umfeld (z. B. durch Praktika oder Werkstudententätigkeiten) Fließende Deutsch- und sehr gute Englischkenntnisse Freude daran, als Trainee direkt Verantwortung für ein Team zu übernehmen und Menschen zu motivieren und entwickeln Du setzt Ideen mit deiner Hands-on-Mentalität in erfolgreiche Projekte um und gehst als Vorbild voran Ein starkes Zahlenverständnis und die Fähigkeit, Probleme frühzeitig zu erkennen Flexibilität und Begeisterung für eine Rolle, die sowohl im Büro als auch im operativen Lagerumfeld stattfindet, inklusive Schichtarbeit Darauf kannst du dich freuen Starte durch - mit uns: Werde Teil unseres internationalen Teams in einem Umfeld, das echtes Wachstum und eine „Act like an Owner“-Mentalität fördert. Bei uns hast du die Chance, Projekte eigenverantwortlich voranzutreiben, neue Ideen zu testen und direkt miterleben zu können, wie deine Arbeit in unserem schnell wachsenden Unternehmen Wirkung zeigt. Nachhaltigkeit als Kern: Werde Teil der Revolution. Du trägst zu einer grüneren Zukunft bei – durch unsere 100 % elektrische Flotte und eine Lieferkette, die Lebensmittelverschwendung reduziert. Die Basics: Wir stellen dir alles für deinen Erfolg bereit – inklusive Laptop und Handy sowie Zugang zu exklusiven Mitarbeiter-Rabatten (Corporate Benefits) für Reisen, Technik und vieles mehr. Zeit zum Auftanken: Mit 30 Urlaubstagen pro Jahr (bei einer 40-Stunden-Woche) sorgst du für den perfekten Ausgleich zwischen Arbeit und Erholung. Verpflegung für Gewinner: Wir kümmern uns um dich. Genieße jeden Tag ein frisches, kostenloses Frühstück und Mittag- oder Abendessen in unserem Fulfilment Center, dazu gibt es reichlich Snacks, Getränke und Obst für den Energiekick zwischendurch. Unvergessliche Momente: Wir sind mehr als nur ein Team. Von unserem legendären jährlichen Ski-Trip über Weihnachtsfeiern bis hin zu Auftritten unserer eigenen Picnic-Band: Wir feiern unsere Erfolge gemeinsam. Wohlbefinden & Gleichgewicht: Wir bieten dir professionelle Unterstützung für deine mentale Gesundheit mit OpenUp. Individuelle Mobilität:Du erhältst einen Firmenwagen (auch zur privaten Nutzung) und kannst zusätzlich unser „Lease-a-Bike“-Programm nutzen. Lebensmittelretter: Hol dir unsere exklusiven \"Too-Good-To-Go\"-Tüten und rette leckere Lebensmittel – nur für unsere Mitarbeitenden! Lerne & wachse: Profitiere von internen Lern- & Entwicklungsmöglichkeiten durch spannende Workshops und intensive Bootcamps, um deine Skills ständig zu erweitern Bist du neugierig?", "summaryDescription" : "Fast Track to Leadership Trainee at Picnic. Skills: Operations Management, Team Leadership, Process Improvement. Onboard and learn fulfillment center. Lead a shift in fulfillment center", "postedDate" : "2026-06-14T19:24:26.439", "createdAt" : "2026-06-14T19:24:26.439", "lastUpdated" : "2026-06-15T21:59:18.600", "ingestTimestamp" : "2026-06-14T19:24:26.439", "mongoId" : "6a2ca43874d8ee00a09b0c0d", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "30k-50k", "hasSalary" : false, "allSkills" : [ "Process simplification", "Bottleneck resolution", "Order process optimization", "Team leadership", "People development", "Leadership", "Mentoring", "Motivation", "Team development", "Operations Management", "Team Leadership", "Process Improvement", "Supply chain management", "Operations management", "Process optimization", "Data analysis", "Project management", "Supply chain", "Fulfillment center operations", "Logistics", "Food waste reduction" ], "skillCount" : 21, "jobCategory" : "operations", "jobSubcategory" : "general", "seniorityLevel" : "Entry", "dataQualityScore" : 1.0, "_score" : 580.9831, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "E-Commerce", "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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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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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. 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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" : 547.7478, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2ca43874d8ee00a09b0c08", "title" : "Fast Track to Leadership Trainee", "company" : "Picnic", "industry" : "Logistics", "salary" : { "min" : 45000.0, "max" : 55000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for entry-level e-commerce roles in Germany, adjusted for a large company size and the specific city tier." }, "location" : "Germany ", "locations" : [ "Germany" ], "timestamp" : "2026-06-15T11:35:27.081", "fingerprint" : "2d8aada6bcd203bb7153e0431858281cf6c37a63513290a45758da1bede06784", "source" : "greenhouse", "language" : "de", "applyUrl" : "https://jobs.picnic.app/nl/vacancies?gh_jid=7730886", "externalId" : "7730886", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Germany", "continent" : "eu", "workMode" : "onsite" } ], "locationText" : "Germany", "employmentType" : "FULL_TIME", "minimumEducation" : "Master's", "experienceMinYears" : 0, "experienceMaxYears" : 2, "experienceLevel" : "Entry", "professionalSkills" : [ "Process management", "Cross-functional coordination", "Vendor management", "Stakeholder management", "Operational metrics", "Resource planning", "Continuous improvement" ], "hardSkillsList" : [ "Data analysis" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Data analysis", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Operations Management, Supply Chain Management, Team Leadership", "majorSkillsList" : [ "Operations Management", "Supply Chain Management", "Team Leadership" ], "coreResponsibilities" : "Plan shifts, Coordinate shifts, Lead teams, Identify optimization potential, Implement improvement projects, Optimize ordering processes, Support new FCs, Support automated FCs", "teamCollaboration" : "Cross-functional teams; International teams", "projectManagementSkills" : [ "Project management" ], "domainKnowledge" : "Supply Chain; Fulfillment Center Operations", "domainList" : [ "supply-chain", "fulfillment-center-operations" ], "domainSpecificKnowledge" : [ "Supply Chain", "Fulfillment Center Operations" ], "continuousLearning" : "Internal learning opportunities; Development opportunities; Workshops; Bootcamps", "innovationCreativity" : "Test new ideas", "problemSolvingSkills" : "Problem identification; Root cause analysis", "specialRequirements" : "Shift work, Office and warehouse environment, Company car, Private car use", "outcomesObjectives" : "Increase productivity; Simplify processes; Solve bottlenecks; Reduce food waste", "qualificationsBasic" : "Master's degree in Logistics, Master's degree in Supply Chain Management, Master's degree in Industrial Engineering, Master's degree in comparable field, First practical experience in supply chain, Fluent German, Very good English skills", "qualificationsPreferred" : "Experience in tech, government, hospitality, logistics, agriculture, manufacturing", "workSiteFlexibility" : "Flexible", "rawDescription" : "Kurz und knapp Du stehst kurz vor deinem Masterabschluss und willst als Graduate mehr als nur einen klassischen Berufseinstieg? Du suchst Verantwortung, Tempo und echte Wirkung in deinem Alltag? Als Fast Track to Leadership Trainee im Bereich Supply Chain und Operations startest du bei Picnic durch: In nur zwei Jahren entwickelst du dich vom Graduate in die Führungsposition als Operations Manager und übernimmst die Verantwortung für Teams, Prozesse und strategische Projekte entlang unserer Supply Chain im Fulfillment. Hands-on, datengetrieben und mit echtem Impact. Das erwartet dich Jahr 1: Operative Grundlagen & Leadership als Operations Supervisor Onboarding & Einstieg: Du startest mit einem strukturierten Onboarding, baust dir ein starkes Netzwerk auf und lernst unser Fulfillment Center (FC) von Grund auf kennen. Schichtleitung im FC: An ca. 3-4 Tagen pro Woche übernimmst du als Operations Supervisor die Verantwortung einer Schicht. Du planst, koordinierst und führst dein Team - und erlebst vom ersten Tag an, wie operative Entscheidungen direkten Einfluss auf unsere Teams und Performance haben. Führung & Coaching: Durch Mentoring, Trainings zu Leadership, Feedback und Motivation lernst du, wie du Menschen entwickelst, Klarheit schaffst und herausfordernde Situationen meisterst. Eigene Projekte mit Impact: Du identifizierst Optimierungspotenziale im operativen Alltag und setzt an deinen 1-2 Projekttagen eigenständig Verbesserungsprojekte um, die Produktivität steigern, Prozesse vereinfachen und Engpässe nachhaltig lösen. Jahr 2: Führung mit Wirkung über Standorte hinweg als Operations Manager (Inter)nationale Perspektive: Ergreife die Chance und bring dein Wissen an anderen Picnic Standorten - national oder international - oder lerne eine andere Abteilung entlang unserer Supply Chain kennen. Du übernimmst Verantwortung in einem neuen Umfeld mit neuen Teams und wächst über dich hinaus. Fokus auf Projekte: Neben deinen ca. 1-2 Schichttagen pro Woche arbeitest du an ca. 3-4 Tagen an standortübergreifenden Initiativen, z. B. bei der Optimierung unserer Bestellprozesse oder bei der Unterstützung neuer (automatisierter) FCs. Mit deinem operativen Know-How und deinem analytischen Blick hebst du unsere Supply Chain auf das nächste Level. Dein nächster Schritt: Nach dem Fast Track stehen dir viele Türen offen: als erfahrener Operations Manager oder in weiteren Positionen innerhalb von Picnic. Das bringst du mit Ein (bald) abgeschlossenes Masterstudium in Logistik, Supply Chain Management, Wirtschaftsingenieurwesen oder einem vergleichbaren Masterstudiengang Erste praktische Erfahrungen im Supply-Chain-Umfeld (z. B. durch Praktika oder Werkstudententätigkeiten) Fließende Deutsch- und sehr gute Englischkenntnisse Freude daran, als Trainee direkt Verantwortung für ein Team zu übernehmen und Menschen zu motivieren und entwickeln Du setzt Ideen mit deiner Hands-on-Mentalität in erfolgreiche Projekte um und gehst als Vorbild voran Ein starkes Zahlenverständnis und die Fähigkeit, Probleme frühzeitig zu erkennen Flexibilität und Begeisterung für eine Rolle, die sowohl im Büro als auch im operativen Lagerumfeld stattfindet, inklusive Schichtarbeit Darauf kannst du dich freuen Starte durch - mit uns: Werde Teil unseres internationalen Teams in einem Umfeld, das echtes Wachstum und eine „Act like an Owner“-Mentalität fördert. Bei uns hast du die Chance, Projekte eigenverantwortlich voranzutreiben, neue Ideen zu testen und direkt miterleben zu können, wie deine Arbeit in unserem schnell wachsenden Unternehmen Wirkung zeigt. Nachhaltigkeit als Kern: Werde Teil der Revolution. Du trägst zu einer grüneren Zukunft bei – durch unsere 100 % elektrische Flotte und eine Lieferkette, die Lebensmittelverschwendung reduziert. Die Basics: Wir stellen dir alles für deinen Erfolg bereit – inklusive Laptop und Handy sowie Zugang zu exklusiven Mitarbeiter-Rabatten (Corporate Benefits) für Reisen, Technik und vieles mehr. Zeit zum Auftanken: Mit 30 Urlaubstagen pro Jahr (bei einer 40-Stunden-Woche) sorgst du für den perfekten Ausgleich zwischen Arbeit und Erholung. Verpflegung für Gewinner: Wir kümmern uns um dich. Genieße jeden Tag ein frisches, kostenloses Frühstück und Mittag- oder Abendessen in unserem Fulfilment Center, dazu gibt es reichlich Snacks, Getränke und Obst für den Energiekick zwischendurch. Unvergessliche Momente: Wir sind mehr als nur ein Team. Von unserem legendären jährlichen Ski-Trip über Weihnachtsfeiern bis hin zu Auftritten unserer eigenen Picnic-Band: Wir feiern unsere Erfolge gemeinsam. Wohlbefinden & Gleichgewicht: Wir bieten dir professionelle Unterstützung für deine mentale Gesundheit mit OpenUp. Individuelle Mobilität:Du erhältst einen Firmenwagen (auch zur privaten Nutzung) und kannst zusätzlich unser „Lease-a-Bike“-Programm nutzen. Lebensmittelretter: Hol dir unsere exklusiven \"Too-Good-To-Go\"-Tüten und rette leckere Lebensmittel – nur für unsere Mitarbeitenden! Lerne & wachse: Profitiere von internen Lern- & Entwicklungsmöglichkeiten durch spannende Workshops und intensive Bootcamps, um deine Skills ständig zu erweitern Bist du neugierig?", "summaryDescription" : "Fast Track to Leadership Trainee at Picnic. Skills: Operations Management, Supply Chain Management, Team Leadership. Plan shifts. Coordinate shifts", "postedDate" : "2026-06-14T04:35:49.829", "createdAt" : "2026-06-14T04:35:49.829", "lastUpdated" : "2026-06-15T11:35:27.081", "ingestTimestamp" : "2026-06-14T04:35:49.829", "mongoId" : "6a2ca43874d8ee00a09b0c08", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "30k-50k", "hasSalary" : false, "allSkills" : [ "Data analysis", "Leadership", "Mentoring", "Operations Management", "Supply Chain Management", "Team Leadership", "Process management", "Cross-functional coordination", "Vendor management", "Stakeholder management", "Operational metrics", "Resource planning", "Continuous improvement", "Project management", "Supply Chain", "Fulfillment Center Operations" ], "skillCount" : 16, "jobCategory" : "operations", "jobSubcategory" : "general", "seniorityLevel" : "Entry", "dataQualityScore" : 1.0, "_score" : 537.6236, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "E-Commerce", "llmIndustryConfidence" : 0.95 }, { "id" : "6a3079f5f292fd229c0365f0", "title" : "Quantitative Researcher - Macro Assets", "company" : "Man Group", "salary" : { "min" : 75000.0, "max" : 110000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Junior Quantitative Researcher in London, adjusted for the financial services industry and a large company size." }, "location" : "London", "locations" : [ "London" ], "timestamp" : "2026-06-16T12:04:26.270", "fingerprint" : "2de1383a9597a3c8edb8df0cca380508a9f66fddb2e459b62ed31e2bf9082317", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/mangroup/jobs/4880305101", "externalId" : "4880305101", "industryFunction" : { }, "structuredLocations" : [ { "city" : "London", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "51.5074456,-0.1277653" } ], "locationText" : "London, United Kingdom", "remoteFriendly" : true, "rawDescription" : "About Man Group Man Group is a global alternative investment management firm focused on pursuing outperformance for sophisticated clients via our Systematic, Discretionary and Solutions offerings. Powered by talent and advanced technology, our single and multi-manager investment strategies are underpinned by deep research and span public and private markets, across all major asset classes, with a significant focus on alternatives. Man Group takes a partnership approach to working with clients, establishing deep connections and creating tailored solutions to meet their investment goals and those of the millions of retirees and savers they represent. Headquartered in London, we manage $227.6 billion* and operate across multiple offices globally. Man Group plc is listed on the London Stock Exchange under the ticker EMG.LN and is a constituent of the FTSE 250 Index. Further information can be found at www.man.com * As at 31 December 2025 The Team AHL Global Macro is the business unit responsible for global macro strategies across all asset classes. The team trade all markets, from liquid to alternative universe, with strategies spanning multiple holding periods. This role sits within the AHL Global Trend And Volatility sector. This role's research mission is to model the behaviour of global macro assets and identify alpha signals, with a particular focus on understanding and modelling what drives trends in macro assets and the timing of this style. The Role You will conduct original alpha research on global macro assets, building and testing predictive signals that inform live trading strategies. You will work across the full research lifecycle — from hypothesis generation and statistical modelling through to implementation and ongoing performance analysis — with direct exposure to live strategy management. Day-to-day you will: Research and develop alpha signals across global macro asset classes, with a focus on trend timing and directional strategies Model the dynamics of macro assets (rates, FX, equities, commodities) to identify exploitable patterns Design and evaluate predictive signals using rigorous statistical and quantitative methods Contribute to portfolio construction and risk analysis across the sector's strategies Monitor live strategy performance and translate observations back into research hypotheses Collaborate with researchers across AHL Global Macro and contribute to the broader research agenda Technology and Business Skills: 2+ years of experience researching alpha signals across macro assets Solid grounding in statistical and mathematical modelling; able to choose the right tool for the right problem Strong Python skills; comfortable working with large financial datasets Understanding of portfolio construction and risk analysis Familiarity with transaction costs and their impact on signal design is a plus Personal Attributes Strong academic record with a degree in a quantitative discipline — Mathematics, Statistics, Physics, Computer Science, Engineering or Economics from a leading university; a PhD or Master's is advantageous Intellectually curious with a genuine interest in financial markets and the macro forces that move them Hands-on and rigorous: you enjoy following an idea all the way from intuition to tested, implemented signal Self-organised with the ability to manage multiple research threads in parallel Clear communicator: able to present quantitative findings concisely and engage constructively with alternative views Collaborative; comfortable working closely with researchers, technologists and portfolio managers Inclusion, Work-Life Balance and Benefits at Man Group You'll thrive in our working environment that champions equality of opportunity. Your unique perspective will contribute to our success, joining a workplace where inclusion is fundamental and deeply embedded in our culture and values. Through our external and internal initiatives, partnerships and programmes, you'll find opportunities to grow, develop your talents, and help foster an inclusive environment for all across our firm and industry. Learn more at www.man.com/diversity. You'll have opportunities to make a difference through our charitable and global initiatives, while advancing your career through professional development, and with flexible working arrangements available too. Like all our people, you'll receive two annual 'Mankind' days of paid leave for community volunteering. Our comprehensive benefits package includes competitive holiday entitlements, pension/401k, life and long-term disability coverage, group sick pay, enhanced parental leave and long-service leave. Depending on your location, you may also enjoy additional benefits such as private medical coverage, discounted gym membership options and pet insurance. Equal Employment Opportunity Policy Man Group provides equal employment opportunities to all applicants and all employees without regard to race, color, creed, national origin, ancestry, religion, disability, sex, gender identity and expression, marital status, sexual orientation, military or veteran status, age or any other legally protected category or status in accordance with applicable federal, state and local laws. Man Group is a Disability Confident Committed employer; if you require help or information on reasonable adjustments as you apply for roles with us, please contact TalentAcquisition@man.com.", "summaryDescription" : "Quantitative Researcher - Macro Assets at Man Group", "postedDate" : "2026-06-16T01:17:44.909", "createdAt" : "2026-06-16T01:17:44.909", "lastUpdated" : "2026-06-16T12:04:26.270", "ingestTimestamp" : "2026-06-16T01:17:44.909", "mongoId" : "6a3079f5f292fd229c0365f0", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "75k-100k", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Junior", "dataQualityScore" : 0.6666667, "_score" : 537.4753, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Financial Services", "llmIndustryConfidence" : 0.98 }, { "id" : "6a3079f5f292fd229c0365ed", "title" : "Quantitative Portfolio Implementation Analyst", "company" : "Man Group", "industry" : "FinTech", "salary" : { "min" : 135000.0, "max" : 195000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-level Quantitative Portfolio Implementation Analyst in Massachusetts, USA, with adjustments for the Financial Services industry and a large company size." }, "location" : "Massachusetts", "locations" : [ "Massachusetts" ], "timestamp" : "2026-06-16T11:33:04.367", "fingerprint" : "0648696c0c236da2f89e083195439ddda04f48311af5fce247e6693f82b0c297", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/mangroup/jobs/4890008101", "externalId" : "4890008101", "industryFunction" : { }, "structuredLocations" : [ { "state" : "Massachusetts", "country" : "United States", "continent" : "na", "workMode" : "onsite" } ], "locationText" : "Massachusetts, United States", "rawDescription" : "About Man Group Man Group is a global alternative investment management firm focused on pursuing outperformance for sophisticated clients via our Systematic, Discretionary and Solutions offerings. Powered by talent and advanced technology, our single and multi-manager investment strategies are underpinned by deep research and span public and private markets, across all major asset classes, with a significant focus on alternatives. Man Group takes a partnership approach to working with clients, establishing deep connections and creating tailored solutions to meet their investment goals and those of the millions of retirees and savers they represent. Headquartered in London, we manage $227.6 billion* and operate across multiple offices globally. Man Group plc is listed on the London Stock Exchange under the ticker EMG.LN and is a constituent of the FTSE 250 Index. Further information can be found at www.man.com * As at 31 December 2025 THE TEAM Man Group's quantitative investment engines, AHL and Numeric, are aligning under Systematic (USD ~138bn AUM). As part of this integration, we are expanding our Investment and Data Implementation (IDI) team, which has supported AHL for many years, into a new Boston-based team supporting the Man Numeric business. The global IDI team spans Hong Kong, Sofia, London and now Boston. The Boston team is responsible for implementing all new business and portfolios (funds, Separately Managed Accounts (SMAs), and investment strategies), maintaining the integrity of systematic models, and steering the long-term development of our trading initiatives. Our mission is to ensure every quantitative strategy is implemented with precision and aligned with its investment objectives, from initial research idea through to the last trade. Though Boston-based and focused primarily on Man Numeric’s content, as part of Systematic, you will be part of a connected global network, sharing tooling, codebase, and implementation capabilities across all four locations. The problems the team solves are diverse, complex, and high-impact. The team is the primary responder when production issues halt the investment managers, requiring rapid diagnosis and resolution without introducing new risks. The team are the operational architects who translate a researcher’s ideal strategy or portfolio into a robust, scalable solution, balancing speed, resilience, and business logic. The team also works closely with other areas such as Portfolio Management and Trading to explain why an algorithm and portfolio optimizer generated specific trades. Finally, we partner with technologists to help design trading architecture that is automated, scalable, and transparent enough for manual intervention when necessary. This role offers exceptional exposure. Man Group's flat structure means your work is widely visible across the group, you will be working with portfolio managers, quantitative researchers, product structuring specialists, and traders, with the opportunity and expectation to contribute, propose solutions, and make decisions regardless of seniority. You’ll be supported throughout and as you build confidence, you will represent the global IDI team on cross-departmental working groups and present findings directly to senior management. THE ROLE We are seeking a highly motivated professional to bridge quantitative research, portfolio management, technology, trading, and middle the ability to interact confidently with portfolio managers and domain experts Dependable judgment under pressure A relentless focus on delivering value to the business and improving implementation processes Advantageous: High level understanding of quantitative investment processes and portfolio construction Experience with portfolio management and/or trading systems, along with proficiency in data analysis and process automation Experience delivering or steering complex projects, such as fund or Separately Managed Account (SMA) launches Commercial experience or a strong interest in using AI tools to drive workflow efficiency and business insights Generalist experience and exposures within buy-side systematic investment (Implementation, Front Office, Middle Office or Trade Operations) Ability to use SQL and an object-oriented language (preferably Python) to investigate data and prototype solutions Proficiency in data reasoning techniques and relevant libraries (e.g., Pandas) The anticipated based salary range for this position is listed below. Compensation packages would also include benefits and a discretionary bonus. This is the base salary range that the Company believes it will pay for this position at the time of this posting based on the location and requirements of the position as well as the skills, qualifications, and experience of the applicant. The Firm reserves the right to modify this pay range at any time. US Pay Range $85,000—$100,000 USD Inclusion, Work-Life Balance and Benefits at Man Group You'll thrive in our working environment that champions equality of opportunity. Your unique perspective will contribute to our success, joining a workplace where inclusion is fundamental and deeply embedded in our culture and values. Through our external and internal initiatives, partnerships and programmes, you'll find opportunities to grow, develop your talents, and help foster an inclusive environment for all across our firm and industry. Learn more at www.man.com/diversity. You'll have opportunities to make a difference through our charitable and global initiatives, while advancing your career through professional development, and with flexible working arrangements available too. Like all our people, you'll receive two annual 'Mankind' days of paid leave for community volunteering. Our comprehensive benefits package includes competitive holiday entitlements, pension/401k, life and long-term disability coverage, group sick pay, enhanced parental leave and long-service leave. Depending on your location, you may also enjoy additional benefits such as private medical coverage, discounted gym membership options and pet insurance. Equal Employment Opportunity Policy Man Group provides equal employment opportunities to all applicants and all employees without regard to race, color, creed, national origin, ancestry, religion, disability, sex, gender identity and expression, marital status, sexual orientation, military or veteran status, age or any other legally protected category or status in accordance with applicable federal, state and local laws. Man Group is a Disability Confident Committed employer; if you require help or information on reasonable adjustments as you apply for roles with us, please contact TalentAcquisition@man.com.", "summaryDescription" : "Quantitative Portfolio Implementation Analyst at Man Group", "postedDate" : "2026-06-16T01:16:52.116", "createdAt" : "2026-06-16T01:16:52.116", "lastUpdated" : "2026-06-16T11:33:04.367", "ingestTimestamp" : "2026-06-16T01:16:52.116", "mongoId" : "6a3079f5f292fd229c0365ed", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 135000, "salaryAnnualMax" : 195000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Mid", "dataQualityScore" : 0.6666667, "_score" : 537.4422, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Financial Services", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c7c2b74d8ee00a094c82c", "title" : "Quantitative Research Intern", "company" : "Man Group", "industry" : "FinTech", "salary" : { "min" : 100000.0, "max" : 150000.0, "currency" : "HKD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market data for entry-level quantitative research internships in Hong Kong, adjusted for the FinTech industry and a large global company like Man Group." }, "location" : "Hong Kong", "locations" : [ "Hong Kong" ], "timestamp" : "2026-06-16T03:10:51.149", "fingerprint" : "38b47e2d37b5d92275bf11ea9647c03a066bb9fd5d5b5207ebf97a49ff2fe9d4", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/mangroup/jobs/4847714101", "externalId" : "4847714101", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Hong Kong", "country" : "Hong Kong", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "22.2818333,114.1582831" } ], "locationText" : "Hong Kong, Hong Kong", "employmentType" : "INTERNSHIP", "minimumEducation" : "Bachelor's", "technicalSkills" : "Python, Pandas, Numpy, Time-series methods, Statistical techniques, Machine learning models", "professionalSkills" : [ "Quantitative research", "Systematic equity research", "Alpha signal development", "Medium-frequency trading", "Statistical arbitrage" ], "hardSkillsList" : [ "Data analysis", "Signal construction", "Backtesting", "Overfitting diagnosis" ], "softSkillsList" : [ "Critical thinking", "Mentorship" ], "hardSkills" : [ { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Signal construction", "level" : "intermediate" }, { "name" : "Backtesting", "level" : "intermediate" }, { "name" : "Overfitting diagnosis", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Critical thinking" }, { "name" : "Mentorship" } ], "majorSkills" : "Quantitative research, Machine learning, Statistical analysis", "majorSkillsList" : [ "Quantitative research", "Machine learning", "Statistical analysis" ], "coreResponsibilities" : "Research time-series methods, Research advanced statistical techniques, Research machine learning models, Extract predictive value from datasets, Analyze noisy datasets, Identify systematic trading opportunities, Develop statistical tools, Develop ML-based tools, Solve data-related problems, Prototype signal variants, Document work cleanly", "teamCollaboration" : "Day-to-day mentorship; Core supervision; High-level exposure; Discuss research results; Present research results; Incorporate feedback", "projectManagementSkills" : [ "End-to-end research project ownership" ], "domainKnowledge" : "Systematic equity; Alpha signals; Medium-frequency; Statistical arbitrage; Predictive value; Systematic trading; Complex datasets; Real-world data", "domainList" : [ "systematic-equity", "alpha-signals", "medium-frequency", "statistical-arbitrage", "predictive-value", "systematic-trading", "complex-datasets", "real-world-data" ], "domainSpecificKnowledge" : [ "Systematic equity", "Alpha signals", "Medium-frequency", "Statistical arbitrage", "Predictive value", "Systematic trading", "Complex datasets", "Real-world data" ], "communicationSkills" : "Communicate complex results; Present research results", "documentationSkills" : "Document work cleanly", "continuousLearning" : "Mentorship", "problemSolvingSkills" : "Rigorous backtesting; Diagnosing overfitting; Questioning assumptions", "outcomesObjectives" : "Iterate towards deployable outcomes", "qualificationsBasic" : "Bachelor's in computer science, Bachelor's in statistics, Bachelor's in machine learning, Bachelor's in signal processing, Bachelor's in optimization, Bachelor's in mathematics, Bachelor's in physics, Master's in computer science, Master's in statistics, Master's in machine learning, Master's in signal processing, Master's in optimization, Master's in mathematics, Master's in physics, PhD in computer science, PhD in statistics, PhD in machine learning, PhD in signal processing, PhD in optimization, PhD in mathematics, PhD in physics, Proficiency in Python, Solid understanding of data structures, Solid understanding of algorithmic complexity, Solid understanding of numerical libraries, Demonstrated ability to conduct research, Ability to communicate complex results", "qualificationsPreferred" : "PhD preferred, Specific ML framework experience, Cloud platform certs", "workSiteFlexibility" : "Flexible", "rawDescription" : "About Man Group Man Group is a global alternative investment management firm focused on pursuing outperformance for sophisticated clients via our Systematic, Discretionary and Solutions offerings. Powered by talent and advanced technology, our single and multi-manager investment strategies are underpinned by deep research and span public and private markets, across all major asset classes, with a significant focus on alternatives. Man Group takes a partnership approach to working with clients, establishing deep connections and creating tailored solutions to meet their investment goals and those of the millions of retirees and savers they represent. Headquartered in London, we manage $227.6 billion* and operate across multiple offices globally. Man Group plc is listed on the London Stock Exchange under the ticker EMG.LN and is a constituent of the FTSE 250 Index. Further information can be found at www.man.com * As at 31 December 2025 Location: Hong Kong SAR Duration: 3–4 months, starting 2026 Eligibility: Final year students (Bachelor's, Master's, or PhD) The Team Join the Specialist Equities team, a small and collaborative systematic equity research group focused on developing medium-frequency statistical arbitrage alpha signals. You will receive day-to-day mentorship from a quantitative researcher in Hong Kong, with core supervision and high-level exposure to portfolio managers and senior management in London. Position Overview You will own a research project end-to-end, taking a disciplined scientific approach to form hypotheses, construct signals, and iterate towards deployable outcomes. The project scope is defined on our side and will be closely tailored to your specific background and strengths once we've met you. During the internship, you will: Research time-series methods, advanced statistical techniques, and machine learning models to extract predictive value from complex datasets. Analyze large, noisy, real-world data sets to identify systematic trading opportunities. Help develop statistical and ML-based tools and techniques to solve complex data-related problems throughout the research process. Typical Day Your primary focus throughout the day will be on researching new statistical techniques, exploring datasets, and prototyping signal variants. Apply critical thinking at every step—rigorously backtesting ideas, diagnosing overfitting, and questioning your own assumptions. Discuss and present research results with your immediate team, portfolio managers, and senior management, actively incorporating their feedback. Document your work cleanly and clearly so colleagues can easily build upon your findings. Required Qualifications Quantitative Background: Pursuing a Bachelor's, Master's, or PhD in computer science, statistics, machine learning, signal processing, optimization, mathematics, physics, or a related STEM subject. Research Excellence: Demonstrated ability to conduct high-quality, in-depth, and rigorous research on real-world data, along with the ability to communicate complex results clearly to both technical peers and senior stakeholders. Programming Proficiency: Strong proficiency in Python, with a solid understanding of data structures, algorithmic complexity, and numerical libraries (e.g., pandas, numpy). Statistical if you require help or information on reasonable adjustments as you apply for roles with us, please contact TalentAcquisition@man.com.", "summaryDescription" : "Quantitative Research Intern at Man Group. Skills: Quantitative research, Machine learning, Statistical analysis. Research time-series methods. Research advanced statistical techniques", "postedDate" : "2026-06-14T19:12:32.693", "createdAt" : "2026-06-14T19:12:32.693", "lastUpdated" : "2026-06-16T03:10:51.149", "ingestTimestamp" : "2026-06-14T19:12:32.693", "mongoId" : "6a2c7c2b74d8ee00a094c82c", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Data analysis", "Signal construction", "Backtesting", "Overfitting diagnosis", "Critical thinking", "Mentorship", "Quantitative research", "Machine learning", "Statistical analysis", "Systematic equity research", "Alpha signal development", "Medium-frequency trading", "Statistical arbitrage", "End-to-end research project ownership", "Systematic equity", "Alpha signals", "Medium-frequency", "Predictive value", "Systematic trading", "Complex datasets", "Real-world data" ], "skillCount" : 21, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 534.1551, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c7c2274d8ee00a094c65c", "title" : "Quantitative Equity Analyst", "company" : "Connor, Clark & Lunn Investment Management", "industry" : "FinTech", "salary" : { "min" : 125000.0, "max" : 200000.0, "currency" : "CAD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Vancouver, British Columbia, Canada", "locations" : [ "Vancouver", "British Columbia", "Canada" ], "timestamp" : "2026-06-16T05:04:26.818", "fingerprint" : "e82eebd1482170b061ef2a188b30356b72d4c7ed4e57d20f5bfef9a25d207f62", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/cclim/jobs/4223791009", "externalId" : "4223791009", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Vancouver", "state" : "British Columbia", "country" : "Canada", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "49.2608724,-123.1139520" } ], "locationText" : "Vancouver, British Columbia, Canada", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "remoteFriendly" : false, "rawDescription" : "We are looking for a Quantitative Equity Analyst to join our Quantitative Equity Team! We are a high-performance team embedded in a top-performing quant fund that manages over $75 billion in financial assets. We are dedicated to the mission-critical operation of our investment engine—a well-tuned machine responsible for generating key decisions that drive trades and investment insights. Leveraging finance skills and cutting-edge technology, we ensure data quality, continuous process improvement, and operational excellence. As a core member of our team, you'll collaborate with investment experts to tackle challenging analytical problems, be accountable to ensure accurate and timely trade generation, and drive operational innovation. Based in West Coast Vancouver, we value mentorship, collaboration, and growth in a supportive and innovative environment. Join us to make a significant impact on our investment engine and overall success. What You Will Do This is an exciting full-time role for individuals who are passionate about learning the quantitative equity investment management business and excited to tackle a broad range of investment, mathematical, and technology challenges. You will start with a comprehensive training program, learning about various elements of quantitative equity investment management and our investment process. You will then continue to a specialized role utilizing data science and process engineering skillsets to accelerate the Quantitative Equities Team’s various investment functions. Your specialized role may involve building, scaling, managing and/or analyzing our quantitative model, portfolios, data assets and optimizers. You will be supported with coaching and mentorship from senior members of the team. We are creating the conditions for you to grow your career steadily over time. Investment Process Management The team you will be joining is our Investment Process Management (IPM) group within our Quantitative Equities Team. IPM plays a central role in building highly scalable, efficient, and robust process management systems. The processes and infrastructure we maintain are critical in the team’s ability to develop systematic investment insights and generate daily trades to capture these insights in portfolios. The opportunity within the IPM group allows ambitious individuals to drive their career growth within IPM, or across the other functions of the Quantitative Equities Team in Research, Portfolio Construction, or Trading. While we take the approach of tailoring the career path for the individual, we have found our functions to cover two main overarching technical skillsets: Process and Reliability Engineering Design, implement and test production processes to run the alpha and risk, portfolio optimization and market implementation processes. Design robust, high performance and effective process orchestration. Monitor production health and respond to critical issues in a timely manner. Effectively communicate real-time production issues to portfolio managers, traders and researchers. Identify computational bottle necks and improve run speeds in production systems. Collaborate with investment teams to ensure their process needs are being met. Find and evaluate areas for process improvements. Assess and evaluate data quality of production processes. Maintain process repos, clean code and tools within production processes. Data Science Construct and run algorithms to explore and assess data effectively. Validate structured and unstructured data sets for data quality. Design and test data loaders and security matching processes and specifications. Perform data analysis and provide data expertise to support researcher’s projects. Facilitate production machine learning operational pipelines with effective and timely auditing and analysis. Enable accessibility and clarity within our data assets through robust documentation and data scrubbing. Develop robust methodologies for assessing and analyzing data in time critical production environments. Respond to and mitigate vendor data issues effectively in a production setting. Collaborate with cross-functional teams to integrate traditional and alternative data into existing analytical frameworks and decision-making processes. Present findings and recommendations to key stakeholders in a clear, concise, and compelling manner. Reasons to Grow Your Career with Us Impact – We help create opportunities for you to leverage your personal strengths to make a positive impact on our business. Culture – Collaboration and innovation are deeply rooted in our culture. We enjoy working together and align our passions in pursuit of a shared objective in every project we undertake. Development – We create conditions for success tailored to each employee through internally developed career development plans. Mentorship – We believe that developing great people is the key to great success. You will have opportunities to share, hear and learn about career experiences from peers and senior team members. Work-Life Balance – Vancouver is surrounded by water, mountains, and cherry blossoms. We work hard in our professional lives but also create space to enjoy our personal lives. What You Bring Analytical Mindset – You think critically and creatively and are adept at balancing intuition with statistical validation. Financial Knowledge – You possess a thorough understanding of (or strong desire to learn) key drivers of business success, including financial theory, economic models, and corporate financial statements. Self-Starter – You are motivated and willing to take personal accountability for quality and timeliness of work. Collaborative Approach – You thrive in a collaborative environment and value shared success. You proactively solicit and provide input and excel at communicating complex and technical concepts. Time Management – You have the ability to manage and prioritize multiple ongoing projects and daily responsibilities. Academic Training – At a minimum, an undergraduate degree in finance, mathematics, statistics, computer science, engineering, or related discipline. Completion of CFA or relevant graduate degree is considered an asset. Industry Experience – You have a passion for quantitative finance, equity investment, data science or related fields. We welcome applications from candidates with different levels of experience, including interns, new graduates, and experienced professionals. The base salary range for full-time roles is $125,000 – $200,000 annually plus a competitive performance bonus. Compensation will be determined based on experience and qualifications. To apply for this position, please submit your resume, cover letter, and academic transcript. #LI-HYBRID #LI-RC1 CC&L Financial Group is committed to creating a diverse and inclusive environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to gender, ethnicity, religion, sexual orientation or expression, disability, or age.  Your application will be reviewed by a member of the hiring team - AI is not used in the screening, assessment or selection of applications at this time.", "summaryDescription" : "Quantitative Equity Analyst at Connor, Clark & Lunn Investment Management", "postedDate" : "2026-06-14T21:47:45.754", "createdAt" : "2026-06-14T21:47:45.754", "lastUpdated" : "2026-06-16T05:04:26.818", "ingestTimestamp" : "2026-06-14T21:47:45.754", "mongoId" : "6a2c7c2274d8ee00a094c65c", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Mid", "dataQualityScore" : 0.7777778, "_score" : 527.98346, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Financial Services", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c7c2274d8ee00a094c65a", "title" : "Quantitative Data Analyst", "company" : "Connor, Clark & Lunn Investment Management", "salary" : { "min" : 125000.0, "max" : 200000.0, "currency" : "CAD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Vancouver, British Columbia, Canada", "locations" : [ "Vancouver", "British Columbia", "Canada" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T01:31:13.653", "fingerprint" : "34ff43fdb29565fe9574fc665d34d1166817e7140448eab71542980c12aae3d4", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/cclim/jobs/4223817009", "externalId" : "4223817009", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Vancouver", "state" : "British Columbia", "country" : "Canada", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "49.2608724,-123.1139520" } ], "locationText" : "Vancouver, British Columbia, Canada", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "technicalSkills" : "SQL, Python, R, Scala, Spark, Dbt, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Dbt Cloud, Delta Lake, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, S3, Glue, SageMaker, Athena, GCP, Vertex AI, Azure, Synapse, ML Studio", "professionalSkills" : [ "Data engineering", "ML/AI", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Modelling skills" ], "hardSkillsList" : [ "Statistical analysis", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference" ], "hardSkills" : [ { "name" : "Statistical analysis", "level" : "intermediate" }, { "name" : "Regression", "level" : "intermediate" }, { "name" : "Classification", "level" : "intermediate" }, { "name" : "Clustering", "level" : "intermediate" }, { "name" : "Time-series analysis", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "majorSkills" : "Data science, Data engineering, ML/AI, Business intelligence", "majorSkillsList" : [ "Data science", "Data engineering", "ML/AI", "Business intelligence" ], "coreResponsibilities" : "Develop and implement data pipelines, Build and maintain data models, Design and deploy machine learning models, Create and maintain BI dashboards, Perform statistical analysis, Collaborate with stakeholders", "teamCollaboration" : "Cross-functional teams; Stakeholders", "toolProficiency" : [ "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy" ], "qualificationsBasic" : "SQL proficiency, 5+ years experience", "qualificationsPreferred" : "PhD preferred, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified certification, Dbt Certified certification", "remoteFriendly" : false, "rawDescription" : "We are looking for a Quantitative Data Analyst to join our Quantitative Equity Team! We are a high-performance team embedded in a top-performing quant fund that manages over $75 billion in financial assets. We are dedicated to the mission-critical operation of our investment engine—a well-tuned machine responsible for generating key decisions that drive trades and investment insights. Leveraging data analytics, finance knowledge and cutting-edge technology, we aim to ensure that new and useful data products are continuously ready for research. Do you love the idea of integrating large proprietary data sources into valuable applications? Are you a wizard at transforming ‘messy reality’ into high quality data assets? As a core member of our team, you will collaborate with investment and data experts to tackle challenging problems, and to continuously expand our capabilities in data. Based on the west coast in Vancouver, we value mentorship, collaboration, and growth in a supportive and innovative environment. Join us to make a significant impact on our investment outcomes and overall success. What You Will Do This is an exciting full-time role for individuals who are enthusiastic about learning the quantitative equity investment management business and excited to tackle a broad range of data, investment, and technology challenges. You will start with a comprehensive training program, learning about various elements of quantitative equity investment management and our investment process. You will then continue to a specialized role utilizing data analytics and data science skillsets to enable the Quantitative Equity Team’s research. Your role will involve identifying and assessing brand new data, data exploration, and proposing robust ways to integrate data products from many sources. You will be supported with coaching and mentorship from senior members of the team, and we will create the conditions for you to grow your career steadily over time. This is an opportunity for ambitious individuals to drive their career growth in data. While we take the approach of tailoring the career path to individual strengths, we expect successful candidates for this role to develop excellence in the following tasks: Create processes to assess, explore, and link billions of data points. Test structured and unstructured data sets for data quality and reliability. Assess new data opportunities for quality and usefulness. Evaluate your data solutions for sensibility, accuracy, and bias. Collaborate with quantitative researchers – support alpha projects with your data expertise. Collaborate with technology specialists – help trade off application performance and operational feasibility. Support production deployments of your work to ensure long-term reliability. Enable clarity of and access to your work through robust documentation and exposition. Present findings and recommendations to key stakeholders in a clear, concise, and compelling manner. What You Bring Analytical Mindset – You think critically and creatively and are adept at balancing intuition with statistical validation. Financial Knowledge – Desire to acquire the financial context needed to understand your stakeholders and make data decisions with impact. Self-Starter – You are motivated and willing to take personal accountability for quality and timeliness of work. Collaborative Approach – You thrive in a collaborative environment and value shared success. You proactively solicit and provide input and excel at communicating complex and technical concepts. Time Management – You are able to manage and prioritize multiple ongoing projects. Academic Training – At a minimum, an undergraduate degree in finance, mathematics, statistics, computer science, engineering, or related discipline. Completion of a relevant graduate degree is considered an asset. We welcome applications from candidates with different levels of experience, including interns, new graduates, and experienced professionals. The base salary range for full-time roles is $125,000 – $200,000 annually plus a competitive performance bonus. Compensation will be determined based on experience and qualifications. To apply for this position, please submit your resume, cover letter and academic transcripts. #LI-HYBRID #LI-RC1 CC&L Financial Group is committed to creating a diverse and inclusive environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to gender, ethnicity, religion, sexual orientation or expression, disability, or age.  Your application will be reviewed by a member of the hiring team - AI is not used in the screening, assessment or selection of applications at this time.", "summaryDescription" : "Quantitative Data Analyst at Connor, Clark & Lunn Investment Management. Skills: Data science, Data engineering, ML/AI, Business intelligence. Develop and implement data pipelines. Build and maintain data models", "postedDate" : "2026-06-14T20:05:45.793", "createdAt" : "2026-06-14T20:05:45.793", "lastUpdated" : "2026-06-16T01:31:13.653", "ingestTimestamp" : "2026-06-14T20:05:45.793", "mongoId" : "6a2c7c2274d8ee00a094c65a", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Statistical analysis", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference", "Data science", "Data engineering", "ML/AI", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Modelling skills", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy" ], "skillCount" : 25, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Mid", "dataQualityScore" : 0.8888889, "_score" : 527.40533, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a3080b2f292fd229c067849", "title" : "Documentation Coordinator", "company" : "The Wonderful Company", "industry" : "Logistics And Supply Chain", "salary" : { "min" : 30000.0, "max" : 45000.0, "currency" : "FJD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Junior Documentation Coordinator in Suva, Fiji, adjusted for the logistics industry and full-time employment." }, "location" : "Suva, Central Division, FJ", "locations" : [ "Suva", "Central Division", "FJ" ], "timestamp" : "2026-06-16T13:35:40.428", "fingerprint" : "a8f9e5ddef9115f029cc195837b0632aca4b74f86ef9a1875a9c773b2e6aa3df", "source" : "smartrecruiters", "language" : "en", "applyUrl" : "https://jobs.smartrecruiters.com/TheWonderfulCompany/744000132078239-documentation-coordinator", "externalId" : "744000132078239", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Suva", "state" : "Central Division", "country" : "Fiji", "continent" : "oc", "source" : "llm", "workMode" : "onsite", "geo" : "-18.1156208,178.4760376" } ], "locationText" : "Suva, Central Division, Fiji", "employmentType" : "FULL_TIME", "experienceMinYears" : 0, "experienceMaxYears" : 2, "experienceLevel" : "entry", "professionalSkills" : [ "Process management", "Cross-functional coordination", "Stakeholder management", "Resource planning", "Continuous improvement" ], "hardSkillsList" : [ "Data entry", "Vessel/ voyage audits" ], "hardSkills" : [ { "name" : "Data entry", "level" : "intermediate" }, { "name" : "Vessel/ voyage audits", "level" : "intermediate" } ], "majorSkills" : "Documentation administration, Process management, Customer support", "majorSkillsList" : [ "Documentation administration", "Process management", "Customer support" ], "coreResponsibilities" : "Process all documentation, Send pre-alert and schedule information, Coordinate with internal departments, Handle documentation submitted by customers, Complete documentation in a timely manner, Download and compile manifest, Compile invoices, Arrange for distribution to authorities, Arrange for distribution to internal customers, Compile manifest, Compile bill of ladings, Compile invoices, Make amendments as required, Enter data of bills, Enter freight details into system, Perform vessel/ voyage audits, Ensure all BOL have been processed, Ensure BOL closed within KPI, Manage end-to-end process, Liaise with Commercial teams, Liaise with Sales teams, Handle rates queries, Prepare pre-receivable advice documentation, Act as first point of contact for customer, Act as first point of contact for customer, Escalate process when necessary, Self-check accuracy of documents, Support internal customers with adhoc requests, Perform other tasks as directed", "teamCollaboration" : "Internal departments; Commercial teams; Sales teams", "domainKnowledge" : "Shipping; Logistics services; Pacific Island markets; Freight; Bills of lading", "domainList" : [ "shipping", "logistics-services", "pacific-island-markets", "freight", "bills-of-lading" ], "domainSpecificKnowledge" : [ "Shipping", "Logistics services", "Pacific Island markets", "Freight", "Bills of lading" ], "toolProficiency" : [ "Microsoft Office Suite", "Cargo Wise" ], "communicationSkills" : "Verbal communication; Written communication", "documentationSkills" : "Document accuracy; Document production", "continuousLearning" : "Opportunity for development; Internal mobility", "specialRequirements" : "Work under pressure, Make sound decisions, Work to changing deadlines, Work under minimal supervision", "outcomesObjectives" : "Improve delivery of functional KPI; Ensure documentation completed timely; Ensure all BOL processed within KPI", "qualificationsBasic" : "Minimum 2 years shipping / freight experience, Tertiary studies in management / business administration, Intermediate proficiency with Microsoft Office Suite, Legal right to live and work in Fiji", "qualificationsPreferred" : "Supply chain desirable, Proficient training experience in Cargo Wise", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Neptune Pacific operates market leading brands in shipping and logistics services across 18 Pacific Island markets. NPDL is the largest carrier in its core Pacific Island markets operating eight container ships and servicing 18 Pacific Island nations. The Documentation Coordinator is responsible for administrating back-office functions of the Customer Experience department. A crucial element of this role is ensuring all documents are produce with a high degree of accuracy and within tight timeframes due to short transit times of the Pacific Island Trades. The Documentation Coordinator will also be required to make system updates according to Company processes to ensure seamless operations and proactively manage issues related to the documentation outputs. It is essential the Documentation Coordinator communicates effectively with internal and external customers. * Process all documentation on behalf of principals and send pre-alert and schedule information to customers * Collaboratively coordinate with all internal departments to improve the delivery of functional KPI * Ensure all documentation submitted by customers is handled with care and completed in a timely manner * Download and compile manifest and invoices and arranging for distribution to local authorities and internal customers * Compiling manifest, bill of ladings and invoices in a timely manner including amendments as required * Responsible for data entry of bills and freight details into system, * Responsible for vessel/ voyage audits to ensure all BOL have been processed and closed within the agreed KPI * Overall accountability of the end-to-end process allocated trade lanes * Liaise with Commercial and Sales teams / Managers on rates queries in accordance with NPDL approval process * Preparing all pre-receivable advice documentation for customers * First point of contact for customer complaints and enquiries related to documentation and escalation process when necessary * Self-checked on accuracy of internal and external documents * Supporting internal customers with adhoc documentation requests * Other tasks as directed ## Qualifications * Tertiary studies in management / business administration with supply chain desirable * Minimum 2 years shipping / freight experience in similar position * Team player with positive, customer-centric attitude * Exceptional communication skills, both verbal and written * Process-oriented approach to work and excellent attention to detail. * Effective Time management and planning skills. * Ability to work under pressure and make sound decisions in fast-paced environment. * Demonstrated adaptability to work to changing deadlines. * Intermediate proficiency with Microsoft Office Suite * Proficient training experience in Cargo Wise desirable * Resilient team player who is goal-orientated and demonstrates a high level of commitment with the ability to work under minimal supervision. ## Additional Information * Competitive benefits package (salary plus bonus). * Opportunity for development and internal mobility. * Wonderful Giving - allowing you to donate company money to a cause of your choice. * Project Wonderful - Staff spend a day in the community helping with various projects. * Company focused on wellness and health If you are a self-starter with an interest in developing your skills in the logistics industry, then this could be you. To be considered for this role you must have the legal right to live and work in Fiji. All your information will be kept confidential according to EEO guidelines. EEO is the law - [click here for more information](https://www.eeoc.gov/sites/default/files/2023-06/22-088EEOCKnowYourRights6.12ScreenRdr.pdf)", "summaryDescription" : "Documentation Coordinator at The Wonderful Company. Skills: Documentation administration, Process management, Customer support. Process all documentation. Send pre-alert and schedule information", "postedDate" : "2026-06-14T21:57:57.000", "createdAt" : "2026-06-16T01:45:16.340", "lastUpdated" : "2026-06-16T13:35:40.428", "ingestTimestamp" : "2026-06-16T01:45:16.340", "mongoId" : "6a3080b2f292fd229c067849", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "30k-50k", "hasSalary" : false, "allSkills" : [ "Data entry", "Vessel/ voyage audits", "Documentation administration", "Process management", "Customer support", "Cross-functional coordination", "Stakeholder management", "Resource planning", "Continuous improvement", "Shipping", "Logistics services", "Pacific Island markets", "Freight", "Bills of lading", "Microsoft Office Suite", "Cargo Wise" ], "skillCount" : 16, "jobCategory" : "operations", "jobSubcategory" : "general", "seniorityLevel" : "Junior", "dataQualityScore" : 1.0, "_score" : 513.14386, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Logistics", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6bb474d8ee00a09141c4", "title" : "Experienced Quantitative Researcher", "company" : "Quantbox Research", "industry" : "FinTech", "salary" : { "min" : 110000.0, "max" : 160000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Senior Quantitative Researcher in Amsterdam, Netherlands, adjusted for FinTech industry and company size." }, "location" : "Amsterdam, North Holland, Netherlands", "locations" : [ "Amsterdam", "North Holland", "Netherlands", "Bengaluru", "Karnataka", "India", "Hong Kong", "Singapore", "Central", "Singapore" ], "timestamp" : "2026-06-15T10:45:08.126", "fingerprint" : "aaf7c88cdb754587e85c91d6839152b00431aeb118836edaf69362e17e8356d8", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/quantboxresearchpte/jobs/4001033101", "externalId" : "4001033101", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Amsterdam", "state" : "North Holland", "country" : "Netherlands", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "52.3730796,4.8924534" } ], "locationText" : "Amsterdam, North Holland, Netherlands", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 2, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, R, Kdb+, C++", "professionalSkills" : [ "Market making", "Systematic alpha research" ], "hardSkillsList" : [ "Quantitative research", "Statistical analysis" ], "hardSkills" : [ { "name" : "Quantitative research", "level" : "intermediate" }, { "name" : "Statistical analysis", "level" : "intermediate" } ], "majorSkills" : "High frequency trading, Quantitative research", "majorSkillsList" : [ "High frequency trading", "Quantitative research" ], "coreResponsibilities" : "Research systematic HFT market making strategies, Develop systematic HFT market making strategies, Leverage existing technology, Leverage existing infrastructure", "teamCollaboration" : "Small collaborative environment; Experienced traders; Experienced developers", "domainKnowledge" : "Proprietary trading; Electronic market making; Asset classes", "domainList" : [ "proprietary-trading", "electronic-market-making", "asset-classes" ], "domainSpecificKnowledge" : [ "Proprietary trading", "Electronic market making", "Asset classes" ], "innovationCreativity" : "Innovate; New technologies; New ideas", "qualificationsBasic" : "Deep experience in high frequency trading, Live high frequency trading experience for at least 2 years, PnL track record with excellent Sharpe ratios", "qualificationsPreferred" : "Degree from top tier college or university a plus", "workSiteFlexibility" : "Flexible", "rawDescription" : "Quantbox is a technology-driven Proprietary trading firm that specializes in systematic alpha research and electronic market-making on various exchanges. We trade across a multitude of asset classes and trading venues with significant market share and are looking for experienced Quantitative Researchers to join our team. As a Quantitative Researcher, you will be working with experienced traders and developers to research and develop new systematic HFT market making strategies leveraging our existing technology and infrastructure. Quantbox encourages Bachelor’s, Master’s and PhD students in computer science, mathematics and related fields to apply. Additional requirements include: Deep experience in high frequency trading Live high frequency trading experience for at least 2 years. PnL track record with excellent Sharpe ratios. Taking pride in building solutions using Python, R, kdb+ or C++ Desire to work in a small collaborative environment Degree from top tier college or university a plus A passion for new technologies and ideas Strong communication skills Quantbox is a place of friends and colleagues, where people convert their passion into action. We believe in togetherness that brings out the best in ourselves and our Company. Our open and casual work culture gives you the space to innovate and deliver. Everyone on the team is approachable. Employee remuneration packages are reviewed regularly to ensure that they remain competitive. In recognition of our employees’ contributions and performance, for full time permanent roles we provide: Competitive compensation 4 Weeks of paid vacation Medical insurance International team outing Quantbox is an equal opportunities employer.", "summaryDescription" : "Experienced Quantitative Researcher at Quantbox Research. Skills: High frequency trading, Quantitative research. Research systematic HFT market making strategies. Develop systematic HFT market making strategies", "postedDate" : "2026-06-14T08:01:11.800", "createdAt" : "2026-06-14T08:01:11.800", "lastUpdated" : "2026-06-15T10:45:08.126", "ingestTimestamp" : "2026-06-14T08:01:11.800", "mongoId" : "6a2c6bb474d8ee00a09141c4", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Quantitative research", "Statistical analysis", "High frequency trading", "Market making", "Systematic alpha research", "Proprietary trading", "Electronic market making", "Asset classes" ], "skillCount" : 8, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 1.0, "_score" : 512.0176, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a306261f292fd229cf9a03a", "title" : "Documentation Coordinator", "company" : "The Wonderful Company", "industry" : "Logistics And Supply Chain", "salary" : { "min" : 30000.0, "max" : 45000.0, "currency" : "FJD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Junior Documentation Coordinator in Suva, Fiji, adjusted for the logistics industry and full-time employment." }, "location" : "Suva, Central Division, FJ", "locations" : [ "Suva", "Central Division", "FJ" ], "timestamp" : "2026-06-16T10:44:17.499", "fingerprint" : "aa64fc2afd94e2466c400089547b771edbf663295cacd6be5cef1df1624adba5", "source" : "smartrecruiters", "language" : "en", "applyUrl" : "https://jobs.smartrecruiters.com/TheWonderfulCompany/744000132078239-documentation-coordinator", "externalId" : "744000132078239", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Suva", "state" : "Central Division", "country" : "Fiji", "continent" : "oc", "source" : "llm", "workMode" : "onsite", "geo" : "-18.1156208,178.4760376" } ], "locationText" : "Suva, Central Division, Fiji", "employmentType" : "FULL_TIME", "experienceMinYears" : 0, "experienceMaxYears" : 2, "experienceLevel" : "entry", "professionalSkills" : [ "Process management", "Cross-functional coordination", "Stakeholder management", "Resource planning", "Continuous improvement" ], "hardSkillsList" : [ "Data entry", "Vessel audits", "Freight details" ], "hardSkills" : [ { "name" : "Data entry", "level" : "intermediate" }, { "name" : "Vessel audits", "level" : "intermediate" }, { "name" : "Freight details", "level" : "intermediate" } ], "majorSkills" : "Documentation administration, Process management, Customer support", "majorSkillsList" : [ "Documentation administration", "Process management", "Customer support" ], "coreResponsibilities" : "Process documentation on behalf principals, Send pre-alert information, Send schedule information, Coordinate with internal departments, Handle documentation submitted by customers, Complete documentation in timely manner, Download manifest, Compile manifest, Arrange distribution to authorities, Arrange distribution to internal customers, Compile manifest, Compile bill of ladings, Compile invoices, Amend documents as required, Enter data of bills, Enter freight details into system, Perform vessel audits, Perform voyage audits, Process BOL, Close BOL within KPI, Manage end-to-end process, Liaise with Commercial teams, Liaise with Sales teams, Prepare pre-receivable advice, Act as first point of contact, Handle customer complaints, Handle customer enquiries, Escalate documentation issues, Self-check accuracy of documents, Support internal customers, Handle adhoc documentation requests, Perform other tasks as directed", "teamCollaboration" : "Internal departments; Commercial teams; Sales teams", "domainKnowledge" : "Shipping; Logistics services; Pacific Island markets; Freight; Bill of ladings", "domainList" : [ "shipping", "logistics-services", "pacific-island-markets", "freight", "bill-of-ladings" ], "domainSpecificKnowledge" : [ "Shipping", "Logistics services", "Pacific Island markets", "Freight", "Bill of ladings" ], "toolProficiency" : [ "Microsoft Office Suite", "Cargo Wise" ], "communicationSkills" : "Verbal communication; Written communication", "documentationSkills" : "Document accuracy; Document production", "continuousLearning" : "Opportunity for development; Internal mobility", "problemSolvingSkills" : "Proactively manage issues", "specialRequirements" : "Legal right to live and work in Fiji", "outcomesObjectives" : "Improve delivery of functional KPI; Ensure documentation completed timely", "qualificationsBasic" : "2 years shipping experience, 2 years freight experience, Tertiary studies in management, Tertiary studies in business administration, Intermediate proficiency Microsoft Office Suite", "qualificationsPreferred" : "Supply chain desirable, Proficient training experience Cargo Wise", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Neptune Pacific operates market leading brands in shipping and logistics services across 18 Pacific Island markets. NPDL is the largest carrier in its core Pacific Island markets operating eight container ships and servicing 18 Pacific Island nations. The Documentation Coordinator is responsible for administrating back-office functions of the Customer Experience department. A crucial element of this role is ensuring all documents are produce with a high degree of accuracy and within tight timeframes due to short transit times of the Pacific Island Trades. The Documentation Coordinator will also be required to make system updates according to Company processes to ensure seamless operations and proactively manage issues related to the documentation outputs. It is essential the Documentation Coordinator communicates effectively with internal and external customers. * Process all documentation on behalf of principals and send pre-alert and schedule information to customers * Collaboratively coordinate with all internal departments to improve the delivery of functional KPI * Ensure all documentation submitted by customers is handled with care and completed in a timely manner * Download and compile manifest and invoices and arranging for distribution to local authorities and internal customers * Compiling manifest, bill of ladings and invoices in a timely manner including amendments as required * Responsible for data entry of bills and freight details into system, * Responsible for vessel/ voyage audits to ensure all BOL have been processed and closed within the agreed KPI * Overall accountability of the end-to-end process allocated trade lanes * Liaise with Commercial and Sales teams / Managers on rates queries in accordance with NPDL approval process * Preparing all pre-receivable advice documentation for customers * First point of contact for customer complaints and enquiries related to documentation and escalation process when necessary * Self-checked on accuracy of internal and external documents * Supporting internal customers with adhoc documentation requests * Other tasks as directed ## Qualifications * Tertiary studies in management / business administration with supply chain desirable * Minimum 2 years shipping / freight experience in similar position * Team player with positive, customer-centric attitude * Exceptional communication skills, both verbal and written * Process-oriented approach to work and excellent attention to detail. * Effective Time management and planning skills. * Ability to work under pressure and make sound decisions in fast-paced environment. * Demonstrated adaptability to work to changing deadlines. * Intermediate proficiency with Microsoft Office Suite * Proficient training experience in Cargo Wise desirable * Resilient team player who is goal-orientated and demonstrates a high level of commitment with the ability to work under minimal supervision. ## Additional Information * Competitive benefits package (salary plus bonus). * Opportunity for development and internal mobility. * Wonderful Giving - allowing you to donate company money to a cause of your choice. * Project Wonderful - Staff spend a day in the community helping with various projects. * Company focused on wellness and health If you are a self-starter with an interest in developing your skills in the logistics industry, then this could be you. To be considered for this role you must have the legal right to live and work in Fiji. All your information will be kept confidential according to EEO guidelines. EEO is the law - [click here for more information](https://www.eeoc.gov/sites/default/files/2023-06/22-088EEOCKnowYourRights6.12ScreenRdr.pdf)", "summaryDescription" : "Documentation Coordinator at The Wonderful Company. Skills: Documentation administration, Process management, Customer support. Process documentation on behalf principals. Send pre-alert information", "postedDate" : "2026-06-14T21:57:57.000", "createdAt" : "2026-06-15T23:55:44.325", "lastUpdated" : "2026-06-16T10:44:17.499", "ingestTimestamp" : "2026-06-15T23:55:44.325", "mongoId" : "6a306261f292fd229cf9a03a", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "30k-50k", "hasSalary" : false, "allSkills" : [ "Data entry", "Vessel audits", "Freight details", "Documentation administration", "Process management", "Customer support", "Cross-functional coordination", "Stakeholder management", "Resource planning", "Continuous improvement", "Shipping", "Logistics services", "Pacific Island markets", "Freight", "Bill of ladings", "Microsoft Office Suite", "Cargo Wise" ], "skillCount" : 17, "jobCategory" : "operations", "jobSubcategory" : "general", "seniorityLevel" : "Junior", "dataQualityScore" : 1.0, "_score" : 508.6103, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Logistics", "llmIndustryConfidence" : 0.95 }, { "id" : "693072a070f0b99d58ffb502", "title" : "Risk Manager, SPI-Gaps", "company" : "ADCI", "industry" : "Corporate Operations, Risk Family, international stores", "salary" : { "min" : 2200000.0, "max" : 3500000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Risk Manager in E-Commerce in Bengaluru, India, adjusted for company size and industry." }, "location" : "Bengaluru, Karnataka, IND", "locations" : [ "Bengaluru, Karnataka, IND" ], "certifications" : [ "CISSP Certification" ], "timestamp" : "2026-06-15T01:03:43.634", "fingerprint" : "0d56eb95ebee571d62f0db8884eff30ab621df269811654dc357fd6f249e850b", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3136591/apply", "externalId" : "52ccfcf3-225f-4a31-bfb4-bf7a1909d291", "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", "experienceLevel" : "Manager", "technicalSkills" : "SQL, Python, R, MATLAB", "professionalSkills" : [ "Risk analysis", "Regulatory compliance", "Data analysis", "Program management", "Project management", "Stakeholder management", "Process improvement", "Risk mitigation", "Abuse prevention", "Fraud prevention", "Data metrics" ], "hardSkillsList" : [ "Data analysis", "Risk analysis", "Regulatory compliance", "Complex data sets", "Confidential information handling", "Quantitative skills", "Repeatable processes", "Automation", "Standardization" ], "softSkillsList" : [ "Integrity", "Discretion", "Leadership", "Negotiation", "Teamwork", "Critical thinking", "Flexibility" ], "hardSkills" : [ { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Risk analysis", "level" : "intermediate" }, { "name" : "Regulatory compliance", "level" : "intermediate" }, { "name" : "Complex data sets", "level" : "intermediate" }, { "name" : "Confidential information handling", "level" : "intermediate" }, { "name" : "Quantitative skills", "level" : "intermediate" }, { "name" : "Repeatable processes", "level" : "intermediate" }, { "name" : "Automation", "level" : "intermediate" }, { "name" : "Standardization", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Integrity" }, { "name" : "Discretion" }, { "name" : "Leadership" }, { "name" : "Negotiation" }, { "name" : "Teamwork" }, { "name" : "Critical thinking" }, { "name" : "Flexibility" } ], "majorSkills" : "Risk management, Data analysis, Project management, Fraud prevention", "majorSkillsList" : [ "Risk management", "Data analysis", "Project management", "Fraud prevention" ], "coreResponsibilities" : "Complete risk analyses, Use complex data sets, Own risk mitigation initiatives, Own risk prevention initiatives, Identify gaps in mechanisms, Identify risks in mechanisms, Identify gaps in policies, Identify risks in policies, Recommend solutions to teams, Use data to discover ways to scale risk, Identify abuse risk, Break problems into manageable pieces, Prioritize meticulously, Deliver results, Conduct large scale deep dives, Derive insights about abuse, Discover solutions, Convey technical knowledge, Deep dive gap root causes, Learn mechanics, Learn partner teams, Learn requirements, Propose mitigation plan, Propose prevention plan, Gain alignment on mitigation plan, Gain alignment on prevention plan, Launch mitigation plan, Launch prevention plan, Monitor mitigation plan, Monitor prevention plan, Communicate progress to stakeholders, Influence stakeholders to adopt, Influence stakeholders to integrate, Influence stakeholders to fix gaps, Allow sunsetting of existing mitigations, Monitor reporting of established mechanisms, Evaluate mechanism effectiveness, Inspect metrics, Inspect anecdotes, Find false positives, Find false negatives, Develop improvements to address misses, Listen, Learn, Engage, Communicate, Execute, Analyze, Influence", "teamCollaboration" : "Interact with partner teams; Interact with stakeholders; Work with operations teams; Work with product teams; Work with risk teams; Work with tech teams; Work with science roles; Cross-functional teams; Partner team stakeholders", "projectManagementSkills" : [ "Program management", "Project management", "Requirements definition", "Schedules" ], "domainKnowledge" : "Fraud; Abuse; Risk domains; Cybersecurity; Data security; Insider risk; Regulatory compliance; Store integrity; E-commerce", "domainList" : [ "fraud", "abuse", "risk-domains", "cybersecurity", "data-security", "insider-risk", "regulatory-compliance", "store-integrity", "e-commerce" ], "domainSpecificKnowledge" : [ "Fraud", "Abuse", "Risk domains", "Cybersecurity", "Data security", "Insider risk", "Regulatory compliance", "Store integrity", "E-commerce" ], "toolProficiency" : [ "SQL", "Python", "R", "MATLAB", "Microsoft Excel" ], "communicationSkills" : "Written communication; Verbal communication; Technical knowledge communication; Executive presentations", "innovationCreativity" : "Create new solutions", "problemSolvingSkills" : "Root cause analysis; Problem solving; Data-driven decision making; Analytical skills; Quantitative skills", "qualificationsBasic" : "Bachelor's degree or equivalent, 5+ years program management, 5+ years project management, Experience using data and metrics, Experience handling confidential information, 5+ years risk analysis, 5+ years regulatory compliance, Proficient in data analysis, Proficient in SQL, Proficient in scripting, High level of integrity, Excellent written communication, Excellent verbal communication, Demonstrated analytical skills, Demonstrated quantitative skills, Proven ability to deliver complex projects, Excellent leadership skills, Excellent negotiation skills, Excellent teamwork skills, Excellent collaboration skills, Critical thinker, Experience implementing repeatable processes, Experience implementing automation, Experience implementing standardization, Proficiency in Microsoft Excel", "qualificationsPreferred" : "5+ years compliance program management, 5+ years legal experience, 5+ years governance experience, 5+ years audit experience, 5+ years risk/loss prevention experience, Experience stakeholder management, Experience building processes, Experience building project management, Experience building schedules, 3+ years program requirements definition, 3+ years data and metrics leveraging, Professional auditing qualification, Risk credentials, Compliance credentials, Experience in e-commerce organizations, Experience in fraud organizations, Experience in compliance organizations, Experience in law enforcement organizations, Experience in intelligence organizations, Experience network engineering, Experience Infosec, Experience software development e-commerce, Experience software for APIs, Experience with software for web scraping, Experience with Threat Intelligence teams, Experience with threat modeling, Familiarity with open source intelligence, Master’s degree data science, Practical experience data science, Master’s degree machine learning, Practical experience machine learning, Experience with AWS cloud solutions, Experience in Data Sciences, Experience in Machine Learning, Experience in Artificial Intelligence, CISSP Certification, Experience in digital forensics, Experience in internal investigations", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "The Special Projects & Investigations team is looking for a motivated, data savvy risk manager to act as a force multiplier supporting our team's mitigation and prevention of fraud and abuse. This position will manage a portfolio of Gap prevention projects aimed at making it harder for bad actors to operate on our stores as well as internal team mechanisms. You will interact with partner teams and stakeholders in operations, product, risk, tech, and science roles in order to execute against your projects. An ideal candidate is highly flexible, a strong communicator, and demonstrates significant bias for action, and loves diving deep. Key job responsibilities Complete risk analyses using complex data sets (SQL, Python, R etc.). • Use high-level judgment to own our most complex risk mitigation and prevention initiatives. • Identify gaps and risks in Amazon's current mechanisms and policies and recommend solutions to product/policy owning teams. • Use data and/or technical skills to discover new ways to scale risk signals resulting in the identification of abuse risk. • Break problems into manageable pieces, meticulously prioritizing, and delivering results in an ambiguous and constantly changing environment. • Conduct large scale deep dives to derive insights about abuse, identifying gaps and risk in Amazon's current mechanisms, systems, and policies. • Discover solutions and convey detailed technical knowledge (verbally, in writing, and via diagram) to engineering, legal, and program/product management teams A day in the life Deep dive gap root causes and learn the mechanics, partner teams, and requirements. Propose and gain alignment on mitigation and prevention plan with partner team stakeholders. Launch, monitor and communicate with stakeholders about the progress of current mitigation and prevention. Influence stakeholders to adopt, integrate, or fix gaps in order to allow sunsetting of existing mitigations. Monitor reporting of established mechanisms and evaluate for effectiveness. Inspect metrics and anecdotes to find false positives and false negatives, then develop improvements to address misses. Listen, learn, engage, communicate, execute, analyze, and influence. About the team The Trust & Store Integrity team (TSI) is responsible for creating a trustworthy shopping experience across Amazon stores worldwide by protecting customers, brands, selling partners and Amazon from fraud, counterfeit, and abuse as well as empowering, providing world‐class support, and building loyalty with Amazon’s millions of selling partners. The Special Projects and Investigations (SPI) team within TSI designs and implements policies, tools and technology innovations to protect customers by identifying and preventing abuse worldwide. Our growth requires highly skilled candidates who move fast, have an entrepreneurial spirit to create new solutions, a tenacity to get things done, and are capable of breaking down and solving complex problems. We value individual expression, respect different opinions, and work together to create a culture where each of us is able to contribute fully. Our unique backgrounds and perspectives strengthen our ability to achieve Amazon's mission of being Earth's most customer-centric company. Our team is comprised of experts in risk domains such as fraud, cybersecurity, data security, insider risk, regulatory compliance, etc. with a strong dependence on data analysis and or technical skills. We complement specialized industry skills with broad risk experiences gathered through years of experience to deliver results. We make mistakes, learn from them, and support each other. Our work is to solve hard puzzles - typically with data and always with a lot persistence and curiosity. If you like the sound of that, come join us. Basic Qualifications: - Bachelor's degree or equivalent - 5+ years of program or project management experience - Experience using data and metrics to determine and drive improvements - Bachelor's degree or equivalent - Experience handling confidential information - 5+ years of relevant experience in risk analysis and/or regulatory compliance. - Highly proficient in data analysis (SQL or experience with multi-terabyte and petabyte relational databases) or scripting (i.e. Python, R, MATLAB). - High level of integrity and discretion to handle confidential information. - Excellent written and verbal communication skills to communicate security and business risk to a broad range of technical and non-technical audiences. - Demonstrated analytical and quantitative skills using hard data and metrics to back up assumptions and develop business cases. - Proven ability to deliver complex projects across multiple teams. - Excellent leadership, negotiation, teamwork, and collaboration skills. - Strong critical thinker with the vision to work both tactically and strategically. - Experience implementing repeatable processes and automation or standardization. - Proficiency in Microsoft Excel. Preferred Qualifications: - 5+ years of compliance program management, legal, governance, audit, risk/loss prevention, or equivalent experience - Experience in stakeholder management, dealing with multiple stakeholders at varied levels of the organization - Experience building processes, project management, and schedules - 3+ years of program requirements definition and data and metrics leveraging to drive improvements experience - Professional auditing qualification, or similar risk or compliance credentials - Experience working in fast paced e-commerce organizations. - Experience working within fraud, compliance, law enforcement, or intelligence organizations. - Experience in adjacent domain areas like network engineering, Infosec, software development for e-commerce, or work involving software for API's or web scraping. - Experience working with Threat Intelligence teams, threat modeling and familiarity with open source intelligence (OSINT). - Master’s degree in or practical experience with data science or machine learning. - Experience with AWS cloud solutions. - Experience in Data Sciences, Machine Learning, or Artificial Intelligence. - CISSP Certification or experience in multiple CISSP knowledge areas - Demonstrated experience in areas such as digital forensics or internal investigations. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.", "summaryDescription" : "Risk Manager, SPI-Gaps at ADCI. Skills: Risk management, Data analysis, Project management, Fraud prevention. Complete risk analyses. 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External partners; Collaborators; Customers; Hardware partners; Across teams", "projectManagementSkills" : [ "Project leadership" ], "domainKnowledge" : "Quantum error correction; Quantum computing; Qubit modalities", "domainList" : [ "quantum-error-correction", "quantum-computing", "qubit-modalities" ], "domainSpecificKnowledge" : [ "Quantum error correction", "Quantum computing", "Qubit modalities" ], "communicationSkills" : "Publications; Talks; Presentations; Written communication; Oral communication", "continuousLearning" : "Learning events; Training; Conference budgets", "innovationCreativity" : "Cutting-edge research projects", "problemSolvingSkills" : "Complex problem solving", "outcomesObjectives" : "Deliver world's first QEC stack; Unlock useful, scalable quantum computing", "qualificationsBasic" : "PhD in mathematics, physics, computer science, or related technical field, Proven ability to undertake high-quality theoretical work, Experience driving research direction, Experience leading multi-person projects, Working knowledge of QEC, Ability to work independently and as part of a team", "qualificationsPreferred" : "Experience undertaking or leading QEC research, Knowledge of qLDPC codes, Understanding of one or more qubit modalities, Experience leading a group of researchers, Knowledge of Python, Knowledge of C++, Track record of winning contracts or grants", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "Cambridge, UK | Full-time | Permanent | Hybrid Salary: £72,000 to £140,000, DOE + Bonus + Benefits The salary range for this role is broad, as we are able to consider varying levels of experience. Any offer made will carefully take into account level of experience (including relevant industry experience), transferable relevant skills and previous relevant achievements. We will also consider part-time applications for this role. Please indicate your preferred working schedule in your cover letter. About us Riverlane’s mission is to master quantum error correction (QEC) and unlock a new age of human progress. From advances in material and climate science, to complex chemistry simulation for new drug design, quantum computers will help humanity solve some of its most important challenges. But without QEC, the industry’s defining technical challenge, such breakthroughs can never be achieved. Riverlane is the world leader in QEC technology. QEC is a complex problem that requires a range of skills, talent and passion. Having raised more than $125M in funding to date to accelerate our cutting-edge R&D in quantum error correction (QEC), Riverlane partners with many of the world’s leading quantum hardware providers and government agencies to make fault-tolerant quantum computing a reality. We’re making remarkable progress and growing fast.  About the role As a Lead Quantum Error Correction Researcher at Riverlane, you won’t just research quantum error correction - you’ll help us build it. Your work will help deliver the world’s first QEC stack and unlock useful, scalable quantum computing. We have a fantastic opportunity to join one of Riverlane’s more science-focused quantum error correction teams, which works to enable large-scale error-corrected quantum computation. This world-class, highly collaborative team brings together mathematicians, physicists, computer scientists and software engineers, working side by side on a diverse portfolio of cutting-edge research projects. In this senior role, you will lead high-impact research projects and manage a small team within a larger, multidisciplinary group. You’ll balance deep, hands-on research with technical leadership, mentoring, and strategic direction. What you will do As a Lead QEC Researcher at Riverlane, your work will vary, but typical activities may include: Pushing the boundaries of quantum error correction (QEC) through hands-on, high-impact research, while coaching and levelling up researchers in your team. Owning and leading multi-person projects end to end, working closely with your team and cross-functional partners across Riverlane. Actively shaping the direction and priorities of QEC research in relevant areas as we scale our technology and roadmap. Translating cutting-edge research into outcomes that move the company forward, contributing directly to Riverlane’s goals and strategy. Line-managing, mentoring and supporting members of your team, helping them to grow and take on increasing responsibility. Building strong relationships with external partners, collaborators, and customers, including hardware partners across all qubit types. Helping define and win new projects by contributing to compelling proposals and funding opportunities. Sharing knowledge and collaborating across teams to rapidly advance our products. Writing and reviewing code for our internal and open-source codebases. Communicating results clearly and decisively through publications, talks, and presentations at leading conferences and workshops. What we need PhD in mathematics, physics, computer science, or a related technical field (or equivalent professional experience) Proven ability to undertake high-quality theoretical work (for example, through publications) Experience driving the direction of scientific or technical research Experience leading projects involving multiple people A collaborative mindset with experience in guiding and mentoring less-experienced colleagues Working knowledge of QEC Ability to work effectively both independently, and as part of a team Strong written and oral communication skills, with the ability to discuss complex ideas with a variety of audiences in a clear way Even better if you have… Experience undertaking or leading QEC research, evidenced by scientific publications Knowledge of qLDPC codes Understanding of one or more qubit modalities Experience leading a group of researchers working across multiple projects, balancing competing priorities Knowledge of Python and/or C++ A track record of winning contracts or grants What can you expect from us A comprehensive benefits package that includes an annual bonus plan, private medical insurance, life insurance, and a contributory pension scheme Equity, so that our team can share in the long-term success of Riverlane 28 days annual leave, plus bank holidays and enhanced family leave A diverse work environment that brings together experts in many fields (including software and hardware development, quantum information theory, physics and maths) and over 20 different nationalities A learning environment that encourages individual, team and company growth and development, including a regular programme of learning events and training and conference budgets How to apply Please upload a CV and covering letter by clicking 'Apply'. Your covering letter should explain why you are applying for the job and what skills and experience you can bring to the role. We review CVs as we receive them and interview as soon as we have applications that look like a good match. We do not use closing dates. So, please apply as soon as possible to avoid missing out on this role. If you have any queries, please contact jobs@riverlane.com. Everyone is welcome at Riverlane. We are an equal opportunities employer and encourage applications from eligible and suitably qualified candidates regardless of age, disability, ethnicity, gender, gender reassignment, religion or belief, sexual orientation, marital or civil partnership status, or pregnancy and maternity/paternity. Women and other underrepresented groups may be less likely to apply for a role unless they meet all or nearly all of the requirements. If this applies to you, we still encourage you to apply - you may be a great fit, even if you don’t meet every single qualification. We’d love to hear from you. If you need any adjustments made to the application or selection process so you can do your best, please let us know. We will be happy to help. GDPR notice: Riverlane collects and processes personal data in accordance with applicable data protection laws. If you are a European Job Applicant see the privacy notice for further details.", "summaryDescription" : "Lead Quantum Error Correction Researcher at Riverlane. Skills: Quantum error correction, Research leadership. Push boundaries of QEC research. 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We combine quantitative research with leading-edge technology to develop differentiated algorithmic investment strategies. A culture of innovation, growth and success through collaboration and mutual respect has enabled us to deliver top tier performance for over two decades. Today, our clients entrust us with over US$60 billion in assets under management across a range of investment mandates. The successful candidate will contribute directly to analysis and research that translate a quantitative investment process into clear, credible content for institutional investors. This is a high-impact role for someone who combines technical depth, sound judgment, and strong communication skills. What You Will Do Working closely with the Quantitative Equity, Client Solutions, and Institutional Sales teams, the Product Analyst will support a broad range of activities, including: Investment Content Development – Develop materials that resonate with internal/external stakeholders by clearly and succinctly relating a complex investment process to developments in markets and portfolios. Business Development – Support initiatives that contribute to the long-term growth and success of the Quantitative Equity platform. Cross-Team Engagement – Build strong relationships with internal stakeholders in order to improve systems, processes, and communications across teams. External Presence – Represent the Quantitative Equity team in meetings with institutional clients, prospects, and consultants. What You Bring Academic background in finance, economics, statistics, mathematics, engineering, data science or a related quantitative discipline. 2 – 5 years of work experience on a quantitative or systematic investment team. Working understanding of factor investing frameworks, portfolio construction and optimization principles, performance attribution and risk decomposition, and empirical research methods. Demonstrated ability to critically and creatively analyze large financial datasets, with a high level of attention to detail. Experience developing external-facing analysis or thought leadership, and ideally presenting this content to stakeholders. Exceptional written and verbal communication skills, with the ability to explain complex quantitative concepts clearly and concisely. A collaborative spirit that enables successful working relationships with a large number of internal and external stakeholders. CFA designation or progress toward completion is an asset. We welcome applications from candidates with different levels of experience. The base salary range is $125,000 – $200,000 annually plus a competitive performance bonus. Compensation will be determined based on experience and qualifications. To apply for this position, please submit your resume, cover letter and academic transcripts. We thank all applicants for their interest, however, only those selected for an interview will be contacted. No telephone calls or agencies will be accepted. Successful applicants must be eligible to work in Canada on their start date. CC&L Financial Group is committed to creating a diverse and inclusive environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to gender, ethnicity, religion, sexual orientation or expression, disability, or age.  Your application will be reviewed by a member of the hiring team - AI is not used in the screening, assessment or selection of applications at this time.", "summaryDescription" : "Product Analyst, Quantitative Equities at Connor, Clark & Lunn Investment Management. Skills: Quantitative analysis, Financial modeling, Data analysis. Develop and maintain quantitative models. 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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" : 491.46783, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "69dde45c2beec4dd3d9a3f9e", "title" : "Postdoctoral Fellow - Computational and Quantitative Medicine", "company" : "City of Hope", "industry" : "Healthcare", "salary" : { "min" : 60000.0, "max" : 85000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Postdoctoral Fellow in the Biotech industry in Monrovia, California, adjusted for entry-level seniority." }, "location" : "United States-California-Monrovia", "locations" : [ "United States-California-Monrovia", "Post-doctoral Research", "Onsite, Days, Days" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T08:17:43.745", "fingerprint" : "5e58bc0dc6aa312fdbc404e13e9157060ab95138ff31668d6bed755cf363f48b", "source" : "taleo", "language" : "en", "applyUrl" : "https://aa067.taleo.net/careersection/ex/jobdetail.ftl?job=210304", "externalId" : "210304", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Monrovia", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "34.1483499,-118.0014517" } ], "locationText" : "Monrovia, California, United States", "minimumEducation" : "PhD", "technicalSkills" : "SQL, Python, R, Scala, Spark, Dbt, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Dbt Cloud, Delta Lake, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, SageMaker, Athena, GCP, Vertex AI, Azure, Synapse, ML Studio", "professionalSkills" : [ "Quantitative analysis", "Data engineering", "Machine learning", "Business intelligence", "Analytics engineering", "Data science" ], "hardSkillsList" : [ "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills" ], "hardSkills" : [ { "name" : "Statistical methods", "level" : "intermediate" }, { "name" : "ML frameworks", "level" : "intermediate" }, { "name" : "BI platforms", "level" : "intermediate" }, { "name" : "Cloud data stacks", "level" : "intermediate" }, { "name" : "Modelling skills", "level" : "intermediate" } ], "majorSkills" : "Data science, Data engineering, Machine learning, Business intelligence", "majorSkillsList" : [ "Data science", "Data engineering", "Machine learning", "Business intelligence" ], "toolProficiency" : [ "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy" ], "qualificationsBasic" : "PhD required, 5+ years experience, SQL proficiency required", "qualificationsPreferred" : "PhD preferred, Specific ML framework experience, Cloud platform certifications", "remoteFriendly" : false, "rawDescription" : "Join the forefront of groundbreaking research at the Beckman Research Institute of City of Hope, where we're changing lives and making a real difference in the fight against cancer, diabetes, and other life-threatening illnesses. Our dedicated and compassionate faculty and staff are driven by a common mission: Contribute to innovative approaches in predicting, preventing, and curing diseases, shaping the future of medicine through cutting-edge research. A Postdoctoral Research Fellow position is open under Dr. Nagarajan Vaidehi within the department of Computational and Quantitative Medicine. This project involves the development and application of interpretable machine learning methods to uncover allosteric regulation of disordered regions in the dynamics of G-protein coupled receptors to enable design of allosteric modulators. You will work on developing design principles of targeted protein degradation in collaboration with Pharma. For more information on Dr. Vaidehi’s lab please visit here . Your qualifications should include: · PhD or M.D. in Chemistry, Physics or Biochemistry with experience in protein dynamics studies. · Knowledgeable about concepts in statistical thermodynamics, in python scripting and C++ programming. · Familiarity with Molecular Dynamics methods and experience in code development is preferred. City of Hope employees pay is based on the following criteria: work experience, qualifications, and work location. City of Hope is an equal opportunity employer. To learn more about our Comprehensive Benefits, please CLICK HERE . United States-California-Monrovia", "summaryDescription" : "Postdoctoral Fellow - Computational and Quantitative Medicine at City of Hope. Skills: Data science, Data engineering, Machine learning, Business intelligence", "createdAt" : "2026-06-14T19:54:56.791", "lastUpdated" : "2026-06-16T08:17:43.745", "ingestTimestamp" : "2026-06-14T19:54:56.791", "mongoId" : "69dde45c2beec4dd3d9a3f9e", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 60000, "salaryAnnualMax" : 85000, "salaryBand" : "50k-75k", "hasSalary" : true, "allSkills" : [ "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills", "Data science", "Data engineering", "Machine learning", "Business intelligence", "Quantitative analysis", "Analytics engineering", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy" ], "skillCount" : 22, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Entry", "dataQualityScore" : 0.6666667, "_score" : 489.9005, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Biotech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c68ca74d8ee00a0904c4f", "title" : "Senior Quantitative Developer", "company" : "TradingHub", "industry" : "Analytics & Data", "salary" : { "min" : 150000.0, "max" : 250000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Quantitative Developer in London, adjusted for executive seniority in the FinTech industry." }, "location" : "London", "locations" : [ "London" ], "timestamp" : "2026-06-15T08:38:53.289", "fingerprint" : "068a8da09ba8516fd5c1e58bc9169e4586a3cf6bef4177590344ca509e7ab9ab", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/tradinghub/36fd290f-9568-4290-9951-ab73a11d8cbe/application", "externalId" : "36fd290f-9568-4290-9951-ab73a11d8cbe", "industryFunction" : { }, "structuredLocations" : [ { "city" : "London", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "51.5074456,-0.1277653" } ], "locationText" : "London, United Kingdom", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "C#, Python, SQL, Postgres", "professionalSkills" : [ "Pricing models", "Financial pricing", "Risk algorithms", "Securities data analysis", "Market dynamics research", "Model validation" ], "hardSkillsList" : [ "Mathematical analysis", "Financial modeling", "Risk assessment", "Database management" ], "hardSkills" : [ { "name" : "Mathematical analysis", "level" : "intermediate" }, { "name" : "Financial modeling", "level" : "intermediate" }, { "name" : "Risk assessment", "level" : "intermediate" }, { "name" : "Database management", "level" : "intermediate" } ], "majorSkills" : "Quantitative development, Financial markets, Software productionisation", "majorSkillsList" : [ "Quantitative development", "Financial markets", "Software productionisation" ], "coreResponsibilities" : "Develop financial pricing libraries, Develop calculators, Develop risk algorithms, Develop pricing algorithms, Analyze securities data, Produce securities data, Research market dynamics, Prototype proprietary models, Test proprietary models, Validate proprietary models, Support junior team members, Coach junior team members", "teamCollaboration" : "Coaching junior members; Working with experts", "projectManagementSkills" : [ "Prioritisation" ], "domainKnowledge" : "Financial markets; Market manipulation; Asset classes; Fixed-income risk; Derivatives; Options; Swaps; Futures", "domainList" : [ "financial-markets", "market-manipulation", "asset-classes", "fixed-income-risk", "derivatives", "options", "swaps", "futures" ], "domainSpecificKnowledge" : [ "Financial markets", "Market manipulation", "Asset classes", "Fixed-income risk", "Derivatives", "Options", "Swaps", "Futures" ], "continuousLearning" : "Study leave", "innovationCreativity" : "Innovation; R&D", "problemSolvingSkills" : "Mathematical skills; Analytical skills", "outcomesObjectives" : "Ensure product capabilities ahead of competitors", "qualificationsBasic" : "Financial markets experience, Proficiency with C#, Proficiency with Python, Exceptional mathematical skills, Exceptional analytical skills, Understanding of market risk, Knowledge of derivatives, Knowledge of database technologies, Deliver projects to deadlines, Excellent prioritisation skills", "qualificationsPreferred" : "Experience within an investment bank, Experience within a pricing-related firm, Understanding of fixed-income risk", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "Compensation: Competitive (Financial Services) About TradingHub Founded in 2010, TradingHub delivers uniquely intelligent trade surveillance software to world leading financial institutions. Developed by market professionals, our solutions use sophisticated modelling techniques to detect single and cross-product market manipulation. With a team of over 150 experts worldwide, TradingHub combines global reach with deep markets expertise to help our customers mitigate financial, regulatory, and reputational risk. The Role We are seeking a Senior Quantitative Developer (VP) to take a leading role in designing, building and validating our pricing models. This includes creating financial pricing libraries for multiple asset classes, calculators and risk algorithms. The successful candidate will combine excellent mathematical skills with proven experience in financial markets and the ability to productionise high-quality software. The capacity to put yourself in the eyes of a trader will be very useful as we continue to ensure our product’s capabilities are ahead of competitors in the market. Responsibilities: - Development of financial pricing libraries, calculators as well as risk/pricing-related algorithms - Using our in-house big data language for the large-scale analysis and production of securities data - Research and development of market dynamics across multiple asset classes - Prototyping, testing, and validation of TradingHub’s proprietary models - supporting and coaching more junior team members Requirements - Proven financial markets experience, ideally within an investment bank or pricing-related firm - Proficiency with C#, Python or another object-oriented programming language - Evidence of exceptional mathematical and analytical skills - A clear understanding of market risk, preferably for fixed-income - Good knowledge of derivatives (e.g. options, swaps, futures etc.) - Good knowledge of database technologies such as SQL, Postgres etc. - Able to deliver projects to agreed deadlines with excellent prioritisation skills Benefits Life at TradingHub is a rewarding journey within a fast-growing company that thrives on innovation and collaboration. By combining the best of technology and global markets, we’re able to solve complex problems together and deliver meaningful results to our customers. Everybody has value to bring, and we welcome individuality as a key driving force behind our collective success. Rooted in everything that we do are our core values: Accountability, Ambition, Partnership and Trust. These values provide the foundation for a sustainable workplace culture that empowers you to grow, contribute, and become your best self. Employee Benefits: - Annual discretionary performance bonus (permanent employees only) - Hybrid working policy - Office lunches twice a week - Private medical insurance + dental cover - Extended parental leave (up to 6 months of fully paid maternity leave) - 25 days annual leave + bank holidays - Enhanced company pension plan - 5 days study leave towards professional qualifications - Salary sacrifice schemes - Death in service coverage Don’t tick every single requirement? Research shows that candidates from under-represented groups are less likely to apply unless they meet all the criteria. We are dedicated to building a diverse, equitable and inclusive workplace, so if this role excites you, please don't let our specification hold you back. Get in touch! TradingHub is an equal opportunities employer. We do not discriminate based on race, religion, ethnic or national origins, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, socio-economic background, responsibilities for dependants, physical or mental disability or other applicable legally protected characteristics. TradingHub selects candidates for interview based solely on their skills, experience and qualifications. We are committed to making our recruitment process accessible to all and we encourage candidates to inform us of any required adjustments. A full copy of our diversity, equity and inclusion policy will be made available to you upon request.", "summaryDescription" : "Senior Quantitative Developer at TradingHub. Skills: Quantitative development, Financial markets, Software productionisation. Develop financial pricing libraries. Develop calculators", "createdAt" : "2026-06-14T02:04:14.207", "lastUpdated" : "2026-06-15T08:38:53.289", "ingestTimestamp" : "2026-06-14T02:04:14.207", "mongoId" : "6a2c68ca74d8ee00a0904c4f", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "150k-200k", "hasSalary" : false, "allSkills" : [ "Mathematical analysis", "Financial modeling", "Risk assessment", "Database management", "Quantitative development", "Financial markets", "Software productionisation", "Pricing models", "Financial pricing", "Risk algorithms", "Securities data analysis", "Market dynamics research", "Model validation", "Prioritisation", "Market manipulation", "Asset classes", "Fixed-income risk", "Derivatives", "Options", "Swaps", "Futures" ], "skillCount" : 21, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Executive", "dataQualityScore" : 0.8888889, "_score" : 489.03098, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2cda0c74d8ee00a0a4a9b7", "title" : "Measurement Analyst", "company" : "Nextdoor", "industry" : "Technology", "salary" : { "min" : 81000.0, "max" : 105000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "San Francisco, California, United States", "locations" : [ "San Francisco", "California", "United States", "Chicago", "Illinois", "United States", "New York", "New York", "United States" ], "timestamp" : "2026-06-16T01:58:38.641", "fingerprint" : "68616fac2842ed528effc6ac3a6a3a8511ffbb8a8109440c50c0002428d2553a", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://about.nextdoor.com/careers-list/?gh_jid=8003675", "externalId" : "8003675", "industryFunction" : { }, "structuredLocations" : [ { "city" : "San Francisco", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "37.7879363,-122.4075201" } ], "locationText" : "San Francisco, California, United States", "employmentType" : "FULL_TIME", "technicalSkills" : "SQL, Python", "professionalSkills" : [ "Measurement strategy", "Data analysis", "Client advising", "Research studies", "Campaign analysis", "Best practices", "Playbook creation" ], "hardSkillsList" : [ "Digital analytics", "Marketing analytics", "Media measurement", "Lift testing", "Incrementality testing", "Attribution", "Foot traffic analysis", "Conversion lift analysis" ], "hardSkills" : [ { "name" : "Digital analytics", "level" : "intermediate" }, { "name" : "Marketing analytics", "level" : "intermediate" }, { "name" : "Media measurement", "level" : "intermediate" }, { "name" : "Lift testing", "level" : "intermediate" }, { "name" : "Incrementality testing", "level" : "intermediate" }, { "name" : "Attribution", "level" : "intermediate" }, { "name" : "Foot traffic analysis", "level" : "intermediate" }, { "name" : "Conversion lift analysis", "level" : "intermediate" } ], "majorSkills" : "Measurement strategy, Data analysis, Client advising", "majorSkillsList" : [ "Measurement strategy", "Data analysis", "Client advising" ], "coreResponsibilities" : "Lead measurement research studies, Manage study process, Deliver study results, Advocate for measurement solutions, Ensure effective implementation, Lead presentation of results, Provide insights, Provide recommendations, Conduct in-depth analyses, Evaluate campaign tactics effectiveness, Create actionable best practices, Create playbooks, Leverage AI tools, Automate analysis tasks, Accelerate data summarization, Explore new AI applications", "teamCollaboration" : "Sales teams; Account management teams; Product teams; Internal teams; Client conversations", "domainKnowledge" : "Measurement landscape; Lift testing; Incrementality testing; Attribution; Foot traffic; Conversion lift; Emerging measurement trends", "domainList" : [ "measurement-landscape", "lift-testing", "incrementality-testing", "attribution", "foot-traffic", "conversion-lift", "emerging-measurement-trends" ], "domainSpecificKnowledge" : [ "Measurement landscape", "Lift testing", "Incrementality testing", "Attribution", "Foot traffic", "Conversion lift", "Emerging measurement trends" ], "toolProficiency" : [ "AI tools", "Claude", "Gemini", "ChatGPT", "Glean" ], "communicationSkills" : "Presenting insights; Presenting recommendations; Senior stakeholder presentations", "documentationSkills" : "Playbook creation", "problemSolvingSkills" : "Solve complex client problems", "specialRequirements" : "In-person events, Team building exercises", "outcomesObjectives" : "Drive impactful results", "qualificationsBasic" : "Bachelor's degree in quantitative field, 0-2 years experience in digital analytics, Understanding of measurement landscape, Demonstrated client service background, Partnering across teams, Comfortable extracting and analyzing datasets, SQL proficiency, Python proficiency", "qualificationsPreferred" : "Master's degree preferred, Specific ML framework experience, Cloud platform certs", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "#TeamNextdoor Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 350,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com. Meet Your Future Neighbors As a Measurement Analyst at Nextdoor, you’ll work at the forefront of strategizing and recommending measurement strategies for our advertisers. As experts in measurement and data, we provide essential technical support to our sales team and deliver value to our clients. Our sales team will count on you to be a trusted adviser to clients while working with them to advise clients on measurement strategies using a mix of first and third party measurement solutions. You will solve complex clients problems and drive impactful results. At Nextdoor, we operate in an AI-first environment and expect every team member to actively use AI tools as part of their workflow. We aren't looking for prompt engineers; we’re looking for people who use tools like Claude, Gemini, ChatGPT, and Glean to challenge their own thinking and take full ownership of AI-assisted outputs. We also offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The hiring team will go over these expectations with you if you are being considered for a role near one of our offices in San Francisco, Los Angeles, Chicago, Dallas, New York, and London. The Impact You’ll Make For a specific set of advertisers, you will lead measurement research studies, managing the entire process from setup through to delivering results Be an advocate for Nextdoor’s measurement solutions within internal sales and account management teams, ensuring their effective implementation in client campaigns Lead the presentation of measurement research results, including insights and recommendations, to clients Conduct in-depth analyses to evaluate the effectiveness of various campaign tactics and create actionable best practices and playbooks Participate in-person Nextdoor events, trainings, off-sites, volunteer days, and other team building exercises Build in-person relationships with team members and contribute to the KIND culture that Nextdoor values Leverage AI tools to enhance day-to-day measurement workflows including automating repetitive analysis tasks, accelerating data summarization and continuously exploring new AI applications relevant to the measurement and analytics space What You’ll Bring To The Team Bachelor’s or Master’s degree in a quantitative field such as statistics, business analytics, or marketing 0-2 years of experience in digital analytics, marketing analytics, media measurement or similar experience at an advertiser, media platform, measurement provider, or media advertising agency An understanding of the measurement landscape, including lift and incrementality testing, attribution, foot traffic and conversion lift, as well as emerging trends in measurement Demonstrated client service background, you thrive in externally facing conversations, working with clients to understand their campaign goals and accordingly recommend measurement opportunities A strong track record partnering across sales, account management and product teams to drive towards a common outcome Clear and concise communication; comfortable with presenting campaign and measurement insights and recommendations to senior stakeholders Ability to handle multiple projects simultaneously in a fast-paced, high-growth environment Comfortable extracting and analyzing large datasets using SQL and or Python A strong passion for Nextdoor's mission Rewards Compensation, benefits, perks, and recognition programs at Nextdoor come together to create one overall rewards package. The starting salary for this role is expected to range from $81,000 - $105,000 on an annualized basis, or potentially greater in the event that your 'level' of proficiency exceeds the level expected for the role. The salary range will be determined by the candidate’s geographic location. We expect to award a meaningful equity grant for this role. With quarterly vesting, your first vest date will take place within 3 months of your start date. When it comes to benefits, we have you covered! Nextdoor employees can choose between a variety of health plans, including a 100% covered employee only plan option, and we also provide a OneMedical membership for concierge care. At Nextdoor, we empower our employees to build stronger local communities. To create a platform where all feel welcome, we want our workforce to reflect the diversity of the neighbors we serve. We encourage everyone interested in our mission to apply. We do not discriminate on the basis of race, gender, religion, sexual orientation, age, or any other trait that unfairly targets a group of people. In accordance with the San Francisco Fair Chance Ordinance, we always consider qualified applicants with arrest and conviction records. For information about our collection and use of applicants’ personal information, please see Nextdoor's Personnel Privacy Notice, found here.", "summaryDescription" : "Measurement Analyst at Nextdoor. Skills: Measurement strategy, Data analysis, Client advising. Lead measurement research studies. Manage study process", "postedDate" : "2026-06-14T19:21:54.924", "createdAt" : "2026-06-14T19:21:54.924", "lastUpdated" : "2026-06-16T01:58:38.641", "ingestTimestamp" : "2026-06-14T19:21:54.924", "mongoId" : "6a2cda0c74d8ee00a0a4a9b7", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 81000, "salaryAnnualMax" : 105000, "salaryBand" : "75k-100k", "hasSalary" : true, "allSkills" : [ "Digital analytics", "Marketing analytics", "Media measurement", "Lift testing", "Incrementality testing", "Attribution", "Foot traffic analysis", "Conversion lift analysis", "Measurement strategy", "Data analysis", "Client advising", "Research studies", "Campaign analysis", "Best practices", "Playbook creation", "Measurement landscape", "Foot traffic", "Conversion lift", "Emerging measurement trends", "AI tools", "Claude", "Gemini", "ChatGPT", "Glean" ], "skillCount" : 24, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Junior", "dataQualityScore" : 0.8888889, "_score" : 486.99277, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c7ec074d8ee00a09537b4", "title" : "Lead Quantum Error Correction Researcher", "company" : "Riverlane", "salary" : { "min" : 145000.0, "max" : 240000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Boston, Massachusetts, United States", "locations" : [ "Boston", "Massachusetts", "United States" ], "timestamp" : "2026-06-16T01:57:38.685", "fingerprint" : "012112152dc25f9b4e7fe162746b5de903564b54bf4a7ce344bbe4d36eba4751", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/riverlane/jobs/4765714101", "externalId" : "4765714101", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Boston", "state" : "Massachusetts", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "42.3588336,-71.0578303" } ], "locationText" : "Boston, Massachusetts, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 8, "experienceMaxYears" : 15, "experienceLevel" : "Lead", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Lead Quantum Error Correction (QEC) Researcher Boston, MA, US | Full-time | Permanent | Hybrid Salary: $145,000 to $240,000 DOE About us Riverlane’s mission is to master quantum error correction (QEC) and unlock a new age of human progress. From advances in material and climate science, to complex chemistry simulation for new drug design, quantum computers will help humanity solve some of its most important challenges. But without QEC, the industry’s defining technical challenge, such breakthroughs can never be achieved. Riverlane is the world leader in QEC technology. QEC is a complex problem that requires a range of skills, talent and passion. Having raised more than $125M in funding to date to accelerate our cutting-edge R&D in quantum error correction (QEC), Riverlane partners with many of the world’s leading quantum hardware providers and government agencies to make fault-tolerant quantum computing a reality. We’re making remarkable progress and growing fast.  About the role As a Lead Quantum Error Correction Researcher at Riverlane, you won’t just research quantum error correction - you’ll help us build it. Your work will help deliver the world’s first QEC stack and unlock useful, scalable quantum computing. We have a fantastic opportunity to join one of Riverlane’s more science-focused quantum error correction teams, which works to enable large-scale error-corrected quantum computation. This world-class, highly collaborative team brings together mathematicians, physicists, computer scientists and software engineers, working side by side on a diverse portfolio of cutting-edge research projects. In this senior role, you will lead high-impact research projects and manage a small team within a larger, multidisciplinary group. You’ll balance deep, hands-on research with technical leadership, mentoring, and strategic direction. What you will do As a Lead QEC Researcher at Riverlane, your work will vary, but typical activities may include: Pushing the boundaries of quantum error correction (QEC) through hands-on, high-impact research, while coaching and levelling up researchers in your team. Owning and leading multi-person projects end to end, working closely with your team and cross-functional partners across Riverlane. Actively shaping the direction and priorities of QEC research in relevant areas as we scale our technology and roadmap. Translating cutting-edge research into outcomes that move the company forward, contributing directly to Riverlane’s goals and strategy. Line-managing, mentoring and supporting members of your team, helping them to grow and take on increasing responsibility. Building strong relationships with external partners, collaborators, and customers, including hardware partners across all qubit types. Helping define and win new projects by contributing to compelling proposals and funding opportunities. Sharing knowledge and collaborating across teams to rapidly advance our products. Writing and reviewing code for our internal and open-source codebases. Communicating results clearly and decisively through publications, talks, and presentations at leading conferences and workshops. What we need PhD in mathematics, physics, computer science, or a related technical field (or equivalent professional experience) Proven ability to undertake high-quality theoretical work (for example, through publications) Experience driving the direction of scientific or technical research Experience leading projects involving multiple people A collaborative mindset with experience in guiding and mentoring less-experienced colleagues Strong, working knowledge of QEC Ability to work effectively both independently, and as part of a team Strong written and oral communication skills, with the ability to discuss complex ideas with a variety of audiences in a clear way Ability to obtain a US gov clearance if required. Even better if you have… Experience undertaking or leading QEC research, evidenced by scientific publications Knowledge of qLDPC codes Understanding of one or more qubit modalities Experience leading a group of researchers working across multiple projects, balancing competing priorities Knowledge of Python and/or C++ A track record of winning contracts or grants What can you expect from us A comprehensive benefits package that includes an annual bonus plan, private medical insurance, life insurance, and 401K contributions Equity, so that our team can share in the long-term success of Riverlane Generous paid time off and enhanced family leave A diverse work environment that brings together experts in many fields (including software and hardware development, quantum information theory, physics and math) and over 20 different nationalities A learning environment that encourages individual, team and company growth and development, including a regular program of learning events and training and conference budgets How to apply Please upload your resume and covering letter by clicking 'Apply Now'. Your cover letter should explain why you are applying for the job and what skills and experience you can bring to the role. We review CVs as we receive them and interview as soon as we have applications that look like a good match. We do not use closing dates. Please apply as soon as possible to avoid missing out on this role. If you have any queries, please contact jobs@riverlane.com. Everyone is welcome at Riverlane. We are an equal opportunity employer and encourage applications from eligible and suitably qualified candidates regardless of age, disability, ethnicity, gender, gender reassignment, religion or belief, sexual orientation, marital or civil partnership status, or pregnancy and maternity/paternity. Women and other underrepresented groups may be less likely to apply for a role unless they meet all or nearly all of the requirements. If this applies to you, we still encourage you to apply - you may be a great fit, even if you don’t meet every single qualification. We’d love to hear from you. If you need any adjustments made to the application or selection process so you can do your best, please let us know. We will be happy to help. GDPR notice: Riverlane collects and processes personal data in accordance with applicable data protection laws. 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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. Generate ideas for new investment insights", "postedDate" : "2026-06-14T04:00:17.587", "createdAt" : "2026-06-14T04:00:17.587", "lastUpdated" : "2026-06-15T05:00:42.980", "ingestTimestamp" : "2026-06-14T04:00:17.587", "mongoId" : "6a2c7c2274d8ee00a094c65e", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Algorithmic strategies", "Predictive modeling", "Quantitative research", "Data science", "Finance", "Securities valuation", "Investment insights", "Financial markets", "Algorithmic investment strategies", "Bloomberg Terminal" ], "skillCount" : 10, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Entry", "dataQualityScore" : 0.7777778, "_score" : 483.36072, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Financial Services", "llmIndustryConfidence" : 0.95 }, { "id" : "6a3058bdf292fd229cf43fd2", "title" : "Roof Measurement Specialist", "company" : "Sourcefit", "salary" : { "min" : 360000.0, "max" : 540000.0, "currency" : "PHP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an entry-level Roof Measurement Specialist in Quezon City, Philippines, adjusted for the real estate industry." }, "location" : "Eastwood Quezon City, PH", "locations" : [ "Eastwood Quezon City", "PH" ], "timestamp" : "2026-06-16T08:48:19.624", "fingerprint" : "d89834b8c3a002cdd23fc46d653aa0528e412cbf2982ad48e41d5b864a62f0a1", "source" : "breezyhr", "language" : "en", "applyUrl" : "https://sourcefit.breezy.hr/p/780acbbaae58-roof-measurement-specialist", "externalId" : "780acbbaae58", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Quezon City", "country" : "Philippines", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "14.6510546,121.0486254" } ], "locationText" : "Quezon City, Philippines", "employmentType" : "FULL_TIME", "coreResponsibilities" : "Measure roofs accurately, Record measurements precisely, Prepare measurement reports, Adhere to safety protocols, Maintain measurement equipment", "domainKnowledge" : "Roof measurement", "domainList" : [ "roof-measurement" ], "domainSpecificKnowledge" : [ "Roof measurement" ], "documentationSkills" : "Measurement reports", "remoteFriendly" : true, "workSiteFlexibility" : "Onsite", "summaryDescription" : "Roof Measurement Specialist at Sourcefit. 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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 Key Skills if you require help or information on reasonable adjustments as you apply for roles with us, please contact TalentAcquisition@man.com.", "summaryDescription" : "Quantitative Developer, Intern at Man Group", "postedDate" : "2026-06-14T03:08:01.891", "createdAt" : "2026-06-14T03:08:01.891", "lastUpdated" : "2026-06-15T12:02:15.073", "ingestTimestamp" : "2026-06-14T03:08:01.891", "mongoId" : "6a2c7c2b74d8ee00a094c829", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Entry", "dataQualityScore" : 0.7777778, "_score" : 480.11237, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "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. 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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. 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Investment teams; Senior members", "projectManagementSkills" : [ "Agile", "Scrum", "JIRA", "Roadmap planning", "Kanban", "PMP" ], "domainKnowledge" : "Quantitative equity investment management; Investment engine; Alpha; Risk; Portfolio optimization; Market implementation; Quantitative model; Portfolios; Data assets; Optimizers; Systematic investment insights; Vendor data", "domainList" : [ "quantitative-equity-investment-management", "investment-engine", "alpha", "risk", "portfolio-optimization", "market-implementation", "quantitative-model", "portfolios", "data-assets", "optimizers", "systematic-investment-insights", "vendor-data" ], "domainSpecificKnowledge" : [ "Quantitative equity investment management", "Investment engine", "Alpha", "Risk", "Portfolio optimization", "Market implementation", "Quantitative model", "Portfolios", "Data assets", "Optimizers", "Systematic investment insights", "Vendor data" ], "toolProficiency" : [ "Dbt Cloud" ], "communicationSkills" : "Executive presentations; Technical documentation; Client meetings", "documentationSkills" : "Technical writing; API documentation; Architecture diagrams", "continuousLearning" : "Mentorship programme; Career development plans", "innovationCreativity" : "Operational innovation; R&D projects; Hackathons; Prototype development; Design thinking", "problemSolvingSkills" : "Root cause analysis; Debugging; Data-driven decision making; Troubleshooting", "outcomesObjectives" : "Accurate trade generation; Timely trade generation", "qualificationsBasic" : "Undergraduate degree in finance, mathematics, statistics, computer science, engineering, or related discipline, SQL proficiency, 5+ years experience", "qualificationsPreferred" : "Completion of CFA, Relevant graduate degree, PhD preferred, Specific ML framework experience, Cloud platform certs", "workSiteFlexibility" : "Flexible", "rawDescription" : "We are looking for a Quantitative Equity Analyst to join our Quantitative Equity Team! We are a high-performance team embedded in a top-performing quant fund that manages over $75 billion in financial assets. We are dedicated to the mission-critical operation of our investment engine—a well-tuned machine responsible for generating key decisions that drive trades and investment insights. Leveraging finance skills and cutting-edge technology, we ensure data quality, continuous process improvement, and operational excellence. As a core member of our team, you'll collaborate with investment experts to tackle challenging analytical problems, be accountable to ensure accurate and timely trade generation, and drive operational innovation. Based in West Coast Vancouver, we value mentorship, collaboration, and growth in a supportive and innovative environment. Join us to make a significant impact on our investment engine and overall success. What You Will Do This is an exciting full-time role for individuals who are passionate about learning the quantitative equity investment management business and excited to tackle a broad range of investment, mathematical, and technology challenges. You will start with a comprehensive training program, learning about various elements of quantitative equity investment management and our investment process. You will then continue to a specialized role utilizing data science and process engineering skillsets to accelerate the Quantitative Equities Team’s various investment functions. Your specialized role may involve building, scaling, managing and/or analyzing our quantitative model, portfolios, data assets and optimizers. You will be supported with coaching and mentorship from senior members of the team. We are creating the conditions for you to grow your career steadily over time. Investment Process Management The team you will be joining is our Investment Process Management (IPM) group within our Quantitative Equities Team. IPM plays a central role in building highly scalable, efficient, and robust process management systems. The processes and infrastructure we maintain are critical in the team’s ability to develop systematic investment insights and generate daily trades to capture these insights in portfolios. The opportunity within the IPM group allows ambitious individuals to drive their career growth within IPM, or across the other functions of the Quantitative Equities Team in Research, Portfolio Construction, or Trading. While we take the approach of tailoring the career path for the individual, we have found our functions to cover two main overarching technical skillsets: Process and Reliability Engineering Design, implement and test production processes to run the alpha and risk, portfolio optimization and market implementation processes. Design robust, high performance and effective process orchestration. Monitor production health and respond to critical issues in a timely manner. Effectively communicate real-time production issues to portfolio managers, traders and researchers. Identify computational bottle necks and improve run speeds in production systems. Collaborate with investment teams to ensure their process needs are being met. Find and evaluate areas for process improvements. Assess and evaluate data quality of production processes. Maintain process repos, clean code and tools within production processes. Data Science Construct and run algorithms to explore and assess data effectively. Validate structured and unstructured data sets for data quality. Design and test data loaders and security matching processes and specifications. Perform data analysis and provide data expertise to support researcher’s projects. Facilitate production machine learning operational pipelines with effective and timely auditing and analysis. Enable accessibility and clarity within our data assets through robust documentation and data scrubbing. Develop robust methodologies for assessing and analyzing data in time critical production environments. Respond to and mitigate vendor data issues effectively in a production setting. Collaborate with cross-functional teams to integrate traditional and alternative data into existing analytical frameworks and decision-making processes. Present findings and recommendations to key stakeholders in a clear, concise, and compelling manner. What You Bring Analytical Mindset – You think critically and creatively and are adept at balancing intuition with statistical validation. Financial Knowledge – You possess a thorough understanding of (or strong desire to learn) key drivers of business success, including financial theory, economic models, and corporate financial statements. Self-Starter – You are motivated and willing to take personal accountability for quality and timeliness of work. Collaborative Approach – You thrive in a collaborative environment and value shared success. You proactively solicit and provide input and excel at communicating complex and technical concepts. Time Management – You have the ability to manage and prioritize multiple ongoing projects and daily responsibilities. Academic Training – At a minimum, an undergraduate degree in finance, mathematics, statistics, computer science, engineering, or related discipline. Completion of CFA or relevant graduate degree is considered an asset. Industry Experience – You have a passion for quantitative finance, equity investment, data science or related fields. Reasons to Grow Your Career with Us Impact – We help create opportunities for you to leverage your personal strengths to make a positive impact on our business. Culture – Collaboration and innovation are deeply rooted in our culture. We enjoy working together and align our passions in pursuit of a shared objective in every project we undertake. Development – We create conditions for success tailored to each employee through internally developed career development plans. Mentorship – We believe that developing great people is the key to great success. You will have opportunities to share, hear and learn about career experiences from peers and senior team members. Work-Life Balance – Vancouver is surrounded by water, mountains, and cherry blossoms. We work hard in our professional lives but also create space to enjoy our personal lives. We welcome applications from candidates with different levels of experience, including interns, new graduates, and experienced professionals. The base salary range for full-time roles is $125,000 – $200,000 annually plus a competitive performance bonus. Compensation will be determined based on experience and qualifications. To apply for this position, please submit your resume, cover letter, and academic transcript. #LI-HYBRID #LI-RC1 CC&L Financial Group is committed to creating a diverse and inclusive environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to gender, ethnicity, religion, sexual orientation or expression, disability, or age.  Your application will be reviewed by a member of the hiring team - AI is not used in the screening, assessment or selection of applications at this time.", "summaryDescription" : "Quantitative Equity Analyst at Connor, Clark & Lunn Investment Management. Skills: Quantitative finance, Data science, Process engineering, Machine learning. Design production processes. Implement production processes", "postedDate" : "2026-06-13T22:20:19.828", "createdAt" : "2026-06-13T22:20:19.828", "lastUpdated" : "2026-06-15T07:14:36.772", "ingestTimestamp" : "2026-06-13T22:20:19.828", "mongoId" : "6a2c7c2274d8ee00a094c65d", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Quantitative analysis", "Statistical validation", "Process management systems", "Algorithmic construction", "Data validation", "Data analysis", "Time series analysis", "Regression", "Classification", "Clustering", "A/B testing", "Causal inference", "Analytical Mindset", "Collaborative Approach", "Time Management", "Quantitative finance", "Data science", "Process engineering", "Machine learning", "Data expertise", "Data quality assessment", "Data scrubbing", "Data integration", "Financial theory", "Economic models", "Corporate financial statements", "Agile", "Scrum", "JIRA", "Roadmap planning", "Kanban", "PMP", "Quantitative equity investment management", "Investment engine", "Alpha", "Risk", "Portfolio optimization", "Market implementation", "Quantitative model", "Portfolios", "Data assets", "Optimizers", "Systematic investment insights", "Vendor data", "CFA", "Dbt Cloud" ], "skillCount" : 46, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Mid", "dataQualityScore" : 0.8888889, "_score" : 476.27475, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6949b14570f0b99d58827180", "title" : "Assistant Track and Field Coach", "company" : "West High School", "industry" : "Sports & Fitness", "salary" : { "min" : 25000.0, "max" : 45000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "The estimation is based on the market baseline for an Entry-level Assistant Track and Field Coach in Wichita, United States, with adjustments for the education industry and part-time employment." }, "location" : "West High School", "locations" : [ "West High School", "820 S. Osage", "67213, Temporary" ], "timestamp" : "2026-06-15T13:18:45.682", "fingerprint" : "beee0192620e68d7cd8377f863c96569b6aabca9bf84f6d3e00c9bf899430200", "source" : "taleo", "language" : "en", "applyUrl" : "https://aa308.taleo.net/careersection/ex/jobdetail.ftl?job=81954", "externalId" : "81954", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Wichita", "state" : "Kansas", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "37.6922361,-97.3375448" } ], "locationText" : "Wichita, Kansas, United States", "employmentType" : "PART_TIME", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Assistant Track and Field Coach If interested, please apply and then contact the Athletic Director at: Micah Womacks mwomacks@usd259.net 316-973-3650", "summaryDescription" : "Assistant Track and Field Coach at West High School", "createdAt" : "2026-06-14T04:34:43.999", "lastUpdated" : "2026-06-15T13:18:45.682", "ingestTimestamp" : "2026-06-14T04:34:43.999", "mongoId" : "6949b14570f0b99d58827180", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 25000, "salaryAnnualMax" : 45000, "salaryBand" : "<30k", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "general", "jobSubcategory" : "general", "seniorityLevel" : "Entry", "dataQualityScore" : 0.6666667, "_score" : 463.56647, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Education", "llmIndustryConfidence" : 0.85 }, { "id" : "6a309695f292fd229c0d50b5", "title" : "Daytime Musculoskeletal Radiologist Partner-Track", "company" : "Diversified Radiology", "industry" : "MSK Daytime", "salary" : { "min" : 500000.0, "max" : 900000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Denver, Colorado", "locations" : [ "Denver, Colorado" ], "timestamp" : "2026-06-16T12:54:01.256", "fingerprint" : "a21760491211d6cfaac8c6285c9d2c282d1c5cd7cc1040df7ee720dc3370a3fc", "source" : "lever", "language" : "en", "applyUrl" : "https://jobs.lever.co/DiversifiedRadiology/50401cd9-14f8-4e93-99ad-441d4907c936/apply", "externalId" : "50401cd9-14f8-4e93-99ad-441d4907c936", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Denver", "state" : "Colorado", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "39.7392364,-104.9848620" } ], "locationText" : "Denver, Colorado, United States", "employmentType" : "FULL_TIME", "remoteFriendly" : true, "rawDescription" : "## Description Diversified Radiology is expanding and seeking a fellowship-trained Musculoskeletal Radiologist to join our highly subspecialized, collegial practice in Denver, Colorado. This is an opportunity to practice high-quality MSK imaging in a supportive environment with a strong focus on subspecialty excellence, efficiency, and collaborative teamwork. Our group offers a well-balanced practice with competitive financial stability, a strong emphasis on quality of life, and the opportunity for partnership for those who desire it. Physicians benefit from 24/7 coverage support, a mature and stable practice infrastructure, and a dedicated team that prioritizes both clinical excellence and sustainable workflow. 100% MSK Volume Shift Hours: Daytime Location: Onsite in Denver, CO and Remote shifts available Start Date: Flexible Employment Options: Full-time or PRN available ## Responsibilities Responsible for 100% MSK imaging interpretation including MRI, CT, radiographs, spine imaging, and general body imaging High-volume, service-oriented practice requiring strong efficiency and patient-focused care ## Requirements Must be Fellowship trained Must be ABR Board Certified or, if recent graduate, Board Eligible Must be skilled or willing to learn arthrogram injections ## Benefits Partner Salary: $500,000+ plus benefits (partners can earn $500-900k+) Additional bonuses for productivity (Associate and Partner Levels) and Retention Monthly fellowship stipend offered to fellows and residents Annual CME/business expense allowance Partnership Track: 1 year for candidates with 2+ years of experience; 2 years for those with less than 2 years of experience. Student loan support Vacation: Generous time off Internal moonlighting opportunities available Moving Allowance if applicable Comprehensive benefits offerings including multiple medical coverage options, HSA and FSA options, supplemental health, dental, vision, life insurance and disability. Retirement savings including individually directed 401k, with company contributions State-of-the-art PACS system and IT, Aidoc , 24/7 IT support, radiology assistant support   Professional liability / malpractice insurance with tail Monthly cell phone / internet reimbursement Home workstation provided (with setup if desired) Cost of needed licenses covered by practice Credentialing and licensing staff that does a majority of the heavy lifting ## Additional Information Diversified Radiology is a thriving and growing 75+ radiologist group founded in 1927 and partnered with Lumexa Imaging. Our practice is dedicated to providing quality, subspecialized care and expertise in Denver, Colorado and throughout the nation via teleradiology. Our practice is truly ‘diversified’ providing subspecialized diagnostic and interventional excellence to improve patient care with different hospital systems, independent outpatient imaging centers, tertiary care centers, community hospitals, specialty practices, and stand-alone ED and urgent care centers in 18 states and growing. Our case mix and complexity rivals that of teaching hospitals, but in a relaxed practice setting that values work/life balance. Lumexa Imaging is an equal opportunity employer. All qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, age, disability, or any other protected status protected by applicable law.", "summaryDescription" : "Daytime Musculoskeletal Radiologist Partner-Track at Diversified Radiology", "postedDate" : "2026-06-15T23:24:57.002", "createdAt" : "2026-06-15T23:24:57.002", "lastUpdated" : "2026-06-16T12:54:01.256", "ingestTimestamp" : "2026-06-16T03:24:13.427", "mongoId" : "6a309695f292fd229c0d50b5", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 500000, "salaryAnnualMax" : 900000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Lead", "dataQualityScore" : 0.7777778, "_score" : 462.42242, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Healthcare", "llmIndustryConfidence" : 0.98 }, { "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. 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"6a2cda0c74d8ee00a0a4a9b6", "title" : "Measurement Analyst", "company" : "Nextdoor", "industry" : "Technology", "salary" : { "min" : 81000.0, "max" : 105000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "San Francisco, California, United States", "locations" : [ "San Francisco", "California", "United States", "Chicago", "Illinois", "United States", "New York", "New York", "United States" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-15T08:32:15.710", "fingerprint" : "d7e3dceb65465e1fd815ee1f33e8c98fe96ac047e740bb412dbdb11509658999", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://about.nextdoor.com/careers-list/?gh_jid=8003681", "externalId" : "8003681", "industryFunction" : { }, "structuredLocations" : [ { "city" : "San Francisco", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "37.7879363,-122.4075201" } ], "locationText" : "San Francisco, California, United States", "employmentType" : "FULL_TIME", "technicalSkills" : "SQL, Python, AI", "professionalSkills" : [ "Measurement strategy", "Client service", "Data analysis" ], "hardSkillsList" : [ "Digital analytics", "Marketing analytics", "Media measurement", "Lift testing", "Incrementality testing", "Attribution modeling", "Foot traffic analysis", "Conversion lift analysis" ], "hardSkills" : [ { "name" : "Digital analytics", "level" : "intermediate" }, { "name" : "Marketing analytics", "level" : "intermediate" }, { "name" : "Media measurement", "level" : "intermediate" }, { "name" : "Lift testing", "level" : "intermediate" }, { "name" : "Incrementality testing", "level" : "intermediate" }, { "name" : "Attribution modeling", "level" : "intermediate" }, { "name" : "Foot traffic analysis", "level" : "intermediate" }, { "name" : "Conversion lift analysis", "level" : "intermediate" } ], "majorSkills" : "Measurement, Data analysis, Client advising", "majorSkillsList" : [ "Measurement", "Data analysis", "Client advising" ], "coreResponsibilities" : "Lead measurement research studies, Manage research process, Deliver research results, Advocate measurement solutions, Implement measurement solutions, Present research results, Conduct in-depth analyses, Evaluate campaign tactics effectiveness, Create best practices, Create playbooks, Leverage AI tools, Automate analysis tasks, Accelerate data summarization, Explore AI applications", "teamCollaboration" : "Work with sales team; Partner with sales; Partner with account management; Partner with product teams", "domainKnowledge" : "Measurement landscape; First party measurement; Third party measurement; AI-first environment", "domainList" : [ "measurement-landscape", "first-party-measurement", "third-party-measurement", "ai-first-environment" ], "domainSpecificKnowledge" : [ "Measurement landscape", "First party measurement", "Third party measurement", "AI-first environment" ], "toolProficiency" : [ "Claude", "Gemini", "ChatGPT", "Glean" ], "communicationSkills" : "Present insights; Present recommendations", "problemSolvingSkills" : "Solve complex problems", "specialRequirements" : "Participate in events, Attend trainings, Attend off-sites, Volunteer days, Team building exercises, Build in-person relationships", "outcomesObjectives" : "Drive impactful results", "qualificationsBasic" : "Bachelor's or Master's degree, 0-2 years experience, SQL proficiency, Python proficiency", "qualificationsPreferred" : "PhD preferred, GCP Professional Data Engineer, AWS Data Analytics, Databricks Certified, Dbt Certified", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "#TeamNextdoor Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 350,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com. Meet Your Future Neighbors As a Measurement Analyst at Nextdoor, you’ll work at the forefront of strategizing and recommending measurement strategies for our advertisers. As experts in measurement and data, we provide essential technical support to our sales team and deliver value to our clients. Our sales team will count on you to be a trusted adviser to clients while working with them to advise clients on measurement strategies using a mix of first and third party measurement solutions. You will solve complex clients problems and drive impactful results. At Nextdoor, we operate in an AI-first environment and expect every team member to actively use AI tools as part of their workflow. We aren't looking for prompt engineers; we’re looking for people who use tools like Claude, Gemini, ChatGPT, and Glean to challenge their own thinking and take full ownership of AI-assisted outputs. We also offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The hiring team will go over these expectations with you if you are being considered for a role near one of our offices in San Francisco, Los Angeles, Chicago, Dallas, New York, and London. The Impact You’ll Make For a specific set of advertisers, you will lead measurement research studies, managing the entire process from setup through to delivering results Be an advocate for Nextdoor’s measurement solutions within internal sales and account management teams, ensuring their effective implementation in client campaigns Lead the presentation of measurement research results, including insights and recommendations, to clients Conduct in-depth analyses to evaluate the effectiveness of various campaign tactics and create actionable best practices and playbooks Participate in-person Nextdoor events, trainings, off-sites, volunteer days, and other team building exercises Build in-person relationships with team members and contribute to the KIND culture that Nextdoor values Leverage AI tools to enhance day-to-day measurement workflows including automating repetitive analysis tasks, accelerating data summarization and continuously exploring new AI applications relevant to the measurement and analytics space What You’ll Bring To The Team Bachelor’s or Master’s degree in a quantitative field such as statistics, business analytics, or marketing 0-2 years of experience in digital analytics, marketing analytics, media measurement or similar experience at an advertiser, media platform, measurement provider, or media advertising agency An understanding of the measurement landscape, including lift and incrementality testing, attribution, foot traffic and conversion lift, as well as emerging trends in measurement Demonstrated client service background, you thrive in externally facing conversations, working with clients to understand their campaign goals and accordingly recommend measurement opportunities A strong track record partnering across sales, account management and product teams to drive towards a common outcome Clear and concise communication; comfortable with presenting campaign and measurement insights and recommendations to senior stakeholders Ability to handle multiple projects simultaneously in a fast-paced, high-growth environment Comfortable extracting and analyzing large datasets using SQL and or Python A strong passion for Nextdoor's mission Rewards Compensation, benefits, perks, and recognition programs at Nextdoor come together to create one overall rewards package. The starting salary for this role is expected to range from $81,000 - $105,000 on an annualized basis, or potentially greater in the event that your 'level' of proficiency exceeds the level expected for the role. The salary range will be determined by the candidate’s geographic location. We expect to award a meaningful equity grant for this role. With quarterly vesting, your first vest date will take place within 3 months of your start date. When it comes to benefits, we have you covered! Nextdoor employees can choose between a variety of health plans, including a 100% covered employee only plan option, and we also provide a OneMedical membership for concierge care. At Nextdoor, we empower our employees to build stronger local communities. To create a platform where all feel welcome, we want our workforce to reflect the diversity of the neighbors we serve. We encourage everyone interested in our mission to apply. We do not discriminate on the basis of race, gender, religion, sexual orientation, age, or any other trait that unfairly targets a group of people. In accordance with the San Francisco Fair Chance Ordinance, we always consider qualified applicants with arrest and conviction records. For information about our collection and use of applicants’ personal information, please see Nextdoor's Personnel Privacy Notice, found here.", "summaryDescription" : "Measurement Analyst at Nextdoor. Skills: Measurement, Data analysis, Client advising. Lead measurement research studies. 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"externalId" : "7898606", "structuredLocations" : [ { "workMode" : "remote" } ], "locationText" : "", "experienceMinYears" : 8, "experienceMaxYears" : 15, "experienceLevel" : "Lead", "technicalSkills" : "SQL, Python, R, Scala, Spark, dbt, Tableau, Power BI, Looker Studio, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, dbt Cloud, Delta Lake, scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, GCP, Azure", "professionalSkills" : [ "Performance reporting", "Operational data", "Financial metrics", "KPI tracking", "Data governance", "Data quality", "Data management", "Reporting accuracy", "Reporting structures", "Data validation", "Performance analysis", "Resource planning", "Workflow optimisation", "Reporting automation", "Reporting accessibility", "Reporting usability", "Client reporting", "Business reviews" ], "hardSkillsList" : [ "Analytical capability", "Operational understanding", "Statistical methods", "ML frameworks", "BI platforms", 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"A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Critical thinking" }, { "name" : "Adaptability" }, { "name" : "Negotiation" }, { "name" : "Mentoring" } ], "majorSkills" : "Data science, Data engineering, ML/AI, Business intelligence, Analytics engineering, Quantitative analysis", "majorSkillsList" : [ "Data science", "Data engineering", "ML/AI", "Business intelligence", "Analytics engineering", "Quantitative analysis" ], "coreResponsibilities" : "Support development of reporting frameworks, Evolve reporting frameworks, Establish consistent tracking approaches, Standardise reporting structures, Standardise KPI definitions, Standardise data taxonomies, Align reporting outputs, Own data integrity, Maintain data integrity, Implement data validation processes, Implement quality assurance processes, Implement reporting accuracy processes, Identify inconsistencies, Identify gaps, Identify risks, Resolve reporting issues, Promote best practice data management, Promote best practice reporting governance, Build regular reporting outputs, Maintain regular reporting outputs, Translate complex datasets, Support governance forums, Support performance reviews, Support client reporting, Analyse trends, Analyse patterns, Work closely with delivery teams, Work closely with operations teams, Work closely with finance teams, Improve visibility across workflows, Improve visibility across resource planning, Improve visibility across performance tracking, Support forecasting, Support planning, Support performance analysis, Identify operational inefficiencies, Identify optimisation opportunities, Contribute to scalable reporting solutions, Contribute to automated workflows, Support integration across reporting tools, Support integration across delivery systems, Support integration across finance platforms, Support integration across workflow trackers, Improve reporting accessibility, Improve reporting automation, Improve reporting usability, Streamline reporting processes, Reduce manual effort, Encourage consistent adoption of measurement frameworks, Encourage consistent adoption of reporting best practices, Partner with internal stakeholders, Understand reporting needs, Understand reporting priorities, Support client-facing reporting requirements, Present clear data, Present accurate data, Present transparent data, Shape performance narratives, Shape reporting materials, Build working relationships, Ensure alignment, Ensure consistency", "teamCollaboration" : "Global teams; Regional teams; Delivery teams; Operations teams; Finance teams; Strategy teams; Internal stakeholders; Client-facing reporting", "domainKnowledge" : "AI technology; Cloud-native architecture; Data governance; Performance metrics; Financial performance", "domainList" : [ "ai-technology", "cloud-native-architecture", "data-governance", "performance-metrics", "financial-performance" ], "domainSpecificKnowledge" : [ "AI technology", "Cloud-native architecture", "Data governance", "Performance metrics", "Financial performance" ], "toolProficiency" : [ "Power BI", "Tableau", "Looker Studio", "Excel" ], "communicationSkills" : "Stakeholder management; Clear communication; Meaningful insight; Practical recommendations; Clear reporting; Concise reporting; Commercially relevant insight; Performance narratives; Data presentation", "continuousLearning" : "Always learning and listening", "innovationCreativity" : "Spark creativity; Innovative results", "problemSolvingSkills" : "Analytical capability; Problem-solving skills; Interpret complex information; Translate complexity", "outcomesObjectives" : "Demonstrate value to clients; Support effective decision-making", "qualificationsBasic" : "5–8+ years’ experience in reporting, analytics, operations, or performance-focused roles, Advanced Excel skills, Experience using reporting and visualisation tools", "qualificationsPreferred" : "PhD preferred, Specific ML framework experience, Cloud platform certs", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Brandtech+ (formerly known as OLIVER+) is a global team of creative thinkers, tech-savvy trendsetters, and production pros specialising in film, CGI, automation, AI, motion design, and digital/print content. We partner with over 300 clients in 40+ countries and counting. Our focus is to connect clients with high-quality solutions, talent and ambitious opportunities worldwide.  As a part of The Brandtech Group, we're at the forefront of leveraging cutting-edge AI technology to revolutionise how we create and deliver work. Our AI solutions enhance efficiency, spark creativity, and drive insightful decision-making, empowering our teams to produce innovative and impactful results. Role: Measurement Lead Location: Remote working until further notice ABOUT THE ROLE: Brandtech+ is evolving how data is structured, governed, and utilised across global client accounts. The Measurement Lead plays a key role in shaping how delivery, operational, financial, and performance data are captured, connected, interpreted, and communicated across The Mix. This role is responsible for driving consistency, accuracy, and transparency across reporting and measurement frameworks, ensuring stakeholders have access to reliable, actionable insights that support effective decision-making and demonstrate value to clients. Working closely with global and regional teams across delivery, operations, finance, and strategy, the Measurement Lead will support the development of scalable reporting structures, robust data governance processes, and integrated performance views across projects, people, finance, and operational metrics. The role is suited to someone who combines strong analytical capability with operational understanding and excellent stakeholder management skills. The successful candidate will be comfortable working across multiple data sources and business functions, translating complexity into clear reporting, meaningful insight, and practical recommendations. This is a hands-on role within a fast-moving global environment, requiring a proactive and detail-oriented individual who can balance strategic thinking with day-to-day execution and continuous improvement. WHAT YOU WILL BE DOING: Measurement & Reporting Frameworks Support the development and ongoing evolution of reporting and measurement frameworks across The Mix. Establish consistent approaches to tracking delivery, operational, financial, and performance metrics. Help standardise reporting structures, KPI definitions, and data taxonomies across markets and teams. Ensure reporting outputs align to client objectives, business priorities, and operational requirements. Data Governance & Quality Control Own and maintain data integrity across reporting inputs and outputs. Develop and implement processes for data validation, quality assurance, and reporting accuracy. Identify inconsistencies, gaps, and risks within reporting structures and work with stakeholders to resolve them. Promote best practice approaches to data management and reporting governance across teams. Performance Reporting & Insight Build and maintain regular reporting outputs for global and regional stakeholders. Translate complex datasets into clear, concise, and commercially relevant insight. Support governance forums, performance reviews, and client reporting through accurate and meaningful performance narratives. Analyse trends and patterns across delivery, utilisation, efficiency, and financial performance metrics. Operational & Commercial Support Work closely with delivery, operations, and finance teams to improve visibility across workflows, resource planning, and performance tracking. Support forecasting, planning, and performance analysis activities through reliable reporting and structured insight. Assist in identifying operational inefficiencies and opportunities for optimisation through data analysis. Contribute to the development of scalable reporting solutions and automated workflows where appropriate. Tools, Systems & Process Improvement Support integration and alignment across reporting tools, delivery systems, finance platforms, and workflow trackers. Help improve reporting accessibility, automation, and usability across teams. Partner with operational and technology stakeholders to streamline reporting processes and reduce manual effort. Encourage consistent adoption of measurement frameworks and reporting best practices globally. Stakeholder & Client Collaboration Partner with internal stakeholders across delivery, strategy, finance, and operations to understand reporting needs and priorities. Support client-facing reporting requirements with clear, accurate, and transparent data presentation. Help shape performance narratives and reporting materials for governance meetings and business reviews. Build strong working relationships across global and regional teams to ensure alignment and consistency. WHAT YOU WILL NEED TO BE GREAT AT THIS ROLE: 5–8+ years’ experience in reporting, analytics, operations, or performance-focused roles within agencies, marketing operations, or in-house environments. Strong analytical and problem-solving skills, with the ability to interpret and communicate complex information clearly. Experience working with performance reporting, operational data, financial metrics, and KPI tracking. Advanced Excel skills and confidence working with large or complex datasets. Experience using reporting and visualisation tools such as Power BI, Tableau, Looker Studio, or equivalent platforms. Strong organisational skills with high attention to detail and accuracy. Ability to manage multiple priorities and stakeholders within fast-paced environments. Excellent communication and stakeholder management skills. A collaborative and proactive approach, with a strong focus on continuous improvement. Req ID - 17490 #LI-DJ1 #LI-REMOTE #LI-Senior #BTG+ Our values shape everything we do: Be Ambitious to succeed  Be Imaginative to push the boundaries of what’s possible  Be Inspirational to do groundbreaking work  Be always learning and listening to understand  Be Results-focused  to exceed expectations  Be actively pro-inclusive and anti-racist across our community, clients and creations  Brandtech+, a part of the Brandtech Group, is an equal opportunity employer committed to creating an inclusive working environment where all employees are encouraged to reach their full potential, and individual differences are valued and respected. All applicants shall be considered for employment without regard to race, ethnicity, religion, gender, sexual orientation, gender identity, age, neurodivergence, disability status, or any other characteristic protected by local laws.  Brandtech+ has set ambitious environmental goals around sustainability, with science-based emissions reduction targets. Collectively, we work towards our mission, embedding sustainability into every department and through every stage of the project lifecycle.'", "summaryDescription" : "Measurement Lead at Brandtech+. Skills: Data science, Data engineering, ML/AI, Business intelligence, Analytics engineering, Quantitative analysis. Support development of reporting frameworks. Evolve reporting frameworks", "postedDate" : "2026-06-12T22:08:19.448", "createdAt" : "2026-06-12T22:08:19.448", "lastUpdated" : "2026-06-15T00:15:45.582", "ingestTimestamp" : "2026-06-12T22:08:19.448", "mongoId" : "6a2c5e8d74d8ee00a08e4dac", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Analytical capability", "Operational understanding", "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills", "Quantitative analysis", "Regression", "Classification", "Clustering", "Time-series", "A/B testing", "Causal inference", "Leadership", "Critical thinking", "Adaptability", "Negotiation", "Mentoring", "Data science", "Data engineering", "ML/AI", "Business intelligence", "Analytics engineering", "Performance reporting", "Operational data", "Financial metrics", "KPI tracking", "Data governance", "Data quality", "Data management", "Reporting accuracy", "Reporting structures", "Data validation", "Performance analysis", "Resource planning", "Workflow optimisation", "Reporting automation", "Reporting accessibility", "Reporting usability", "Client reporting", "Business reviews", "AI technology", "Cloud-native architecture", "Performance metrics", "Financial performance", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "dbt Certified", "Power BI", "Tableau", "Looker Studio", "Excel" ], "skillCount" : 54, "jobCategory" : "other", "jobSubcategory" : "analytics-", "dataQualityScore" : 0.8888889, "_score" : 449.23444, "daysOld" : 2, "hasLocation" : true, "hasGeo" : false }, { "id" : "6a2c6b1a74d8ee00a0910403", "title" : "Quantitative Researcher - Deep Learning", "company" : "XTX Markets", "industry" : "FinTech", "salary" : { "min" : 150000.0, "max" : 250000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Quantitative Researcher in FinTech in London, UK, adjusted for company size and industry." }, "location" : "London, England, United Kingdom", "locations" : [ "London", "England", "United Kingdom" ], "timestamp" : "2026-06-15T13:20:22.233", "fingerprint" : "c609b569ead99a4f801b7c654f23ddec92e724cf64d212180fcb95f9e62381d7", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/xtxmarketstechnologies/jobs/7770152003", "externalId" : "7770152003", "industryFunction" : { }, "structuredLocations" : [ { "city" : "London", "state" : "England", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "51.5074456,-0.1277653" } ], "locationText" : "London, England, United Kingdom", "employmentType" : "FULL_TIME", "minimumEducation" : "PhD", "technicalSkills" : "Python, R, Scala, Spark, SQL, Deep learning, Machine learning, Statistics, Mathematics, Computer science, Physics", "professionalSkills" : [ "Research taste", "Mathematical depth", "Modelling practical", "Experimental taste", "Hypothesis formation", "Test design", "Ambiguous results reading", "Evidence interpretation", "Intellectual honesty" ], "hardSkillsList" : [ "Time-series prediction", "Cross-sectional prediction", "Representation improvement", "Objective improvement", "Optimization improvement", "Regularisation improvement", "Uncertainty estimation", "Evaluation methods", "Scaling improvement", "Robustness improvement", "Distribution shift handling", "Market feedback integration" ], "hardSkills" : [ { "name" : "Time-series prediction", "level" : "intermediate" }, { "name" : "Cross-sectional prediction", "level" : "intermediate" }, { "name" : "Representation improvement", "level" : "intermediate" }, { "name" : "Objective improvement", "level" : "intermediate" }, { "name" : "Optimization improvement", "level" : "intermediate" }, { "name" : "Regularisation improvement", "level" : "intermediate" }, { "name" : "Uncertainty estimation", "level" : "intermediate" }, { "name" : "Evaluation methods", "level" : "intermediate" }, { "name" : "Scaling improvement", "level" : "intermediate" }, { "name" : "Robustness improvement", "level" : "intermediate" }, { "name" : "Distribution shift handling", "level" : "intermediate" }, { "name" : "Market feedback integration", "level" : "intermediate" } ], "majorSkills" : "Deep learning, ML research, Forecasting systems, Modelling", "majorSkillsList" : [ "Deep learning", "ML research", "Forecasting systems", "Modelling" ], "coreResponsibilities" : "Do original research, Improve forecasting systems, Improve trading systems, Design deep learning models, Train deep learning models, Improve representations, Improve objectives, Improve optimisation, Improve regularisation, Improve uncertainty estimates, Improve evaluation methods, Improve scaling, Make models robust, Work with engineers, Work with technologists, Turn research into production, Learn market structure, Ask better modelling questions", "teamCollaboration" : "Flat team; Ideas challenged directly", "domainKnowledge" : "Financial instruments; Market structure; Trading systems; Time scales; Microseconds to weeks; Non-stationary data; Weak signals; Short-lived signals; Model evaluation; Costs; Latency; Risk; Capacity", "domainList" : [ "financial-instruments", "market-structure", "trading-systems", "time-scales", "microseconds-to-weeks", "non-stationary-data", "weak-signals", "short-lived-signals", "model-evaluation", "costs", "latency", "risk", "capacity" ], "domainSpecificKnowledge" : [ "Financial instruments", "Market structure", "Trading systems", "Time scales", "Microseconds to weeks", "Non-stationary data", "Weak signals", "Short-lived signals", "Model evaluation", "Costs", "Latency", "Risk", "Capacity" ], "problemSolvingSkills" : "Test hypotheses; Read ambiguous results; Change mind quickly", "qualificationsBasic" : "Deep practical understanding of modern deep learning, Mathematical and statistical foundations, Excellent programming ability, Comfort working close to implementation details, Good experimental taste, High standards, Intellectual honesty", "qualificationsPreferred" : "PhD or equivalent research experience, Experience training large models, Building ML systems at scale, Time-series modelling experience, Online learning experience, Continual learning experience, Reinforcement learning experience, Causal inference experience, Probabilistic modelling experience, Optimisation experience, Compilers experience, HPC experience, Low-latency systems experience, Experience taking research beyond prototype", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "The Firm XTX Markets is a leading algorithmic trading firm. We build models that forecast prices for more than 53,000 financial instruments across equities, fixed income, currencies, commodities and crypto. Those forecasts are used to trade on exchanges and other venues, and to provide liquidity to clients. The firm trades over $250bn a day across 35 countries, with over 300 people in London, Singapore, New York, Paris, Bristol, Mumbai, Yerevan and Kajaani. XTX is a technology business. Trading here is driven by research, large-scale computation and careful engineering. Over the last decade our models have moved from the econometric methods that gave the firm its name, through trees and neural networks, to modern deep learning. We expect that evolution to continue, and we are looking for researchers who can push it. The research platform is large by any standard, and particularly unusual in trading: well over 25,000 GPUs and more than 1 exabyte of usable storage, with further compute being built in Finland. The point is simple: good ideas should not be bottlenecked by data, infrastructure or compute. The Team This role sits in XTX's central Quantitative Research team, the group responsible for the firm's core forecasting research. The team reports directly to XTX's founder and is intentionally flat. There is little ceremony and little hierarchy; researchers are expected to have ideas, test them properly, argue from evidence and get useful work into the system. The work is modern ML research, not finance by another name. You do not need to have worked in trading. The best candidates usually have strong research taste, mathematical depth and the ability to make models work in practice. An interest in markets helps, because the domain is full of useful structure, but trading intuition can be built here. The Role Trading is a hard setting for machine learning in ways that are not always obvious from outside the industry. The data is enormous, messy, non-stationary and produced by other agents. Signals are weak and often short-lived. Evaluation is unforgiving: costs, latency, risk and capacity all matter, and a model that looks good in a backtest may still be useless in the market. The time scales also range from microseconds to weeks, so there is no single right abstraction. Your job will be to do original research that improves XTX's forecasting and trading systems. Depending on your background, that may mean: Designing and training deep learning models for large-scale time-series and cross-sectional prediction. Improving representations, objectives, optimisation, regularisation, uncertainty estimates, evaluation methods or scaling. Making models more robust under distribution shift and feedback from the market. Working with engineers and trading technologists to turn research into production systems. Learning enough market structure to ask better modelling questions. This is not about applying standard methods to tidy datasets. It is a place to do serious ML research on difficult data, with enough compute and infrastructure for ambitious ideas to be tested properly. What We Are Looking For Evidence of original technical ability in ML, statistics, mathematics, computer science, physics or another quantitative field. Publications are one route, but not the only one; strong industrial research or major open-source contributions can also be good evidence. Deep practical understanding of modern deep learning: architectures, objectives, optimisation, scaling, evaluation and failure modes. Strong mathematical and statistical foundations. Excellent programming ability and comfort working close to the details of implementation. Good experimental taste: forming hypotheses, designing clean tests, reading ambiguous results and changing your mind quickly when the evidence changes. High standards, intellectual honesty and the ability to work in a flat team where ideas are challenged directly. No finance background is needed; the important thing is being willing to learn the domain. Beneficial Experience PhD or equivalent research experience in a relevant technical field. Experience training large models or building ML systems at meaningful scale. Work in time-series modelling, online or continual learning, reinforcement learning, causal inference, probabilistic modelling, optimisation, compilers, HPC or low-latency systems. Experience taking research beyond a prototype. Benefits Key benefits include: Onsite gym, sauna and fitness classes. Extensive medical benefits, including onsite doctor and therapist. Breakfast and lunch provided daily. Support for caregivers, including emergency dependent care. King's Cross office. 25 days paid holiday per year, plus statutory holidays and paid sick days. Generous pension contributions.", "summaryDescription" : "Quantitative Researcher - Deep Learning at XTX Markets. Skills: Deep learning, ML research, Forecasting systems, Modelling. Do original research. Improve forecasting systems", "postedDate" : "2026-06-14T07:54:53.456", "createdAt" : "2026-06-14T07:54:53.456", "lastUpdated" : "2026-06-15T13:20:22.233", "ingestTimestamp" : "2026-06-14T07:54:53.456", "mongoId" : "6a2c6b1a74d8ee00a0910403", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "150k-200k", "hasSalary" : false, "allSkills" : [ "Time-series prediction", "Cross-sectional prediction", "Representation improvement", "Objective improvement", "Optimization improvement", "Regularisation improvement", "Uncertainty estimation", "Evaluation methods", "Scaling improvement", "Robustness improvement", "Distribution shift handling", "Market feedback integration", "Deep learning", "ML research", "Forecasting systems", "Modelling", "Research taste", "Mathematical depth", "Modelling practical", "Experimental taste", "Hypothesis formation", "Test design", "Ambiguous results reading", "Evidence interpretation", "Intellectual honesty", "Financial instruments", "Market structure", "Trading systems", "Time scales", "Microseconds to weeks", "Non-stationary data", "Weak signals", "Short-lived signals", "Model evaluation", "Costs", "Latency", "Risk", "Capacity" ], "skillCount" : 38, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "_score" : 448.14398, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c7fe674d8ee00a0956d12", "title" : "Associate/AVP, Quantitative Strategies Group", "company" : "Cross River", "industry" : "Banking", "salary" : { "min" : 150000.0, "max" : 190000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Fort Lee, New Jersey, United States", "locations" : [ "Fort Lee", "New Jersey", "United States" ], "timestamp" : "2026-06-16T03:27:15.846", "fingerprint" : "4f97d293c1f8b38069b3ea3bc93c6b9f40783a060390e5524c40c2a045012cdc", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://www.crossriver.com/greenhouse?gh_jid=7770430003", "externalId" : "7770430003", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Fort Lee", "state" : "New Jersey", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.8509333,-73.9701382" } ], "locationText" : "Fort Lee, New Jersey, United States", "employmentType" : "FULL_TIME", "rawDescription" : "Who We Are Cross River builds the infrastructure behind the world’s most innovative financial products. Our technology and capital solutions power payments, cards, lending, and digital asset capabilities that move money safely, instantly, and inclusively — trusted by leading fintechs, enterprises, and disruptors across the globe. Our mission is simple: to build the financial infrastructure that expands access and opportunity for all. Guided by a culture of collaboration, curiosity, and purpose, Cross River has been named one of American Banker’s Best Places to Work in Fintech year after year. Whether you’re designing code, solving regulatory puzzles, or developing strategy, you’ll join a team where innovation and integrity drive everything we do — and where your work helps shape the future of finance. What We're Looking For The Quantitative Strategies Group (QSG) at Cross River is seeking an Associate/AVP, Quant Strategist to join its growing team. The team sits within the Capital Solutions Group (CSG) and serves as a centralized function for investment intelligence and quantitative decision making across investment, structuring, and portfolio management initiatives. The role sits at the intersection of structured finance, investment strategy, and advanced analytics - bridging the gap between raw data and capital decisions. The role will work closely with the Structured Products Group (SPG) and Principal Finance Group (PFG) to support investment underwriting, new deal origination, term ABS issuance/advisory, and active portfolio management. The ideal candidate will combine strong analytical and technical skills with commercial judgement - someone who can analyze collateral performance, understand relevant risk factors, form a view on underlying assets, build scalable analytical tools, and translate complex quantitative outputs into clear investment recommendations. This is a high-impact role for someone who wants exposure to live transactions, structured credit markets, and data-driven decision-making. Responsibilities: Work closely with SPG and PFG to provide quantitative and analytical insights across investment opportunities, ABS securitizations, and structured credit transactions - from deal inception through execution Support capital commitment objectives through systematic underwriting of investment opportunities. Deliver refined and polished views on analytics, base/stress assumptions, and cashflow models that accurately capture the risk/reward dynamics of potential trades Support investment advisory mandates by producing market-ready analytics, comparative deal analyses, and performance benchmarks that help articulate differentiated value proposition to clients and counterparties Develop and maintain analytical frameworks to evaluate collateral pools, form views on key pricing assumptions (e.g., prepayment speeds, default/loss curves), and deliver actionable insights that inform deal economics and structuring decisions Translate quantitative outputs into clear/concise narratives and presentation materials that support pitch efforts, client discussions, and internal committees Partner with the team to identify, prioritize, and integrate high-impact AI use cases across workflows. Explore and implement AI-driven approaches to collateral analysis using LLMs and Python based tools Partner with other functions within CSG and across the bank to ensure consistency in assumptions, methodologies, and market intelligence used across the group Qualifications: Master’s degree in financial engineering, math, statistics, computer science, or any another quantitative/analytical field required 3+ years of experience in Structured Finance, Securitization, or broader Fixed Income markets is required. Direct exposure to ABS products is strongly preferred Strong understanding of cashflow modeling and securitization mechanics - deal waterfalls, tranche structures, collateral performance analysis is preferred Proficiency in advanced excel & programming is required for this role. Hands-on experience in Python & SQL is critical for success Excellent communication and presentation skills - ability to distill complex analytics into clear, persuasive narratives for both internal stakeholders and external counterparties Builder's mentality - someone who doesn't just use existing tools but actively seeks to improve how the team works by introducing new technologies, frameworks, and AI-driven efficiencies Ability to thrive in a fast-paced, deal-driven environment with competing priorities and tight turnaround times Detail-oriented with strong organizational skills and a proactive, ownership-driven mindset #LI-JJ1 #LI-Hybrid #LI-Onsite Salary Range: $150,000.00 - $190,000.00 Cross River is an Equal Opportunity Employer. Cross River does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need. By submitting your application, you give Cross River permission to email, call, or text you using the contact details provided. We will only contact you with job related information.", "summaryDescription" : "Associate/AVP, Quantitative Strategies Group at Cross River", "postedDate" : "2026-06-14T21:31:33.591", "createdAt" : "2026-06-14T21:31:33.591", "lastUpdated" : "2026-06-16T03:27:15.846", "ingestTimestamp" : "2026-06-14T21:31:33.591", "mongoId" : "6a2c7fe674d8ee00a0956d12", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 150000, "salaryAnnualMax" : 190000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Mid", "dataQualityScore" : 0.7777778, "_score" : 442.0202, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.97 }, { "id" : "6a2c7ec074d8ee00a09537b7", "title" : "Principal Investigator, Quantum Error Correction", "company" : "Riverlane", "industry" : "Technology", "salary" : { "min" : 180000.0, "max" : 245000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Boston, Massachusetts, United States", "locations" : [ "Boston", "Massachusetts", "United States" ], "timestamp" : "2026-06-15T07:46:50.364", "fingerprint" : "2ef706bf95472e14f1cef12872c23d56ee7e56a72b878758f2d3ef682d543056", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/riverlane/jobs/4787546101", "externalId" : "4787546101", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Boston", "state" : "Massachusetts", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "42.3588336,-71.0578303" } ], "locationText" : "Boston, Massachusetts, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Quantum error correction, Quantum computing", "professionalSkills" : [ "Scientific inventiveness", "Technical leadership", "Technical direction", "External research programs", "Funding proposals", "Oral evaluations" ], "hardSkillsList" : [ "Fault-tolerant architectures", "Decoding algorithms", "Noise characterization", "System-level performance analysis" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Fault-tolerant architectures", "level" : "intermediate" }, { "name" : "Decoding algorithms", "level" : "intermediate" }, { "name" : "Noise characterization", "level" : "intermediate" }, { "name" : "System-level performance analysis", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Quantum error correction, Research leadership", "majorSkillsList" : [ "Quantum error correction", "Research leadership" ], "coreResponsibilities" : "Conceive original research, Conduct original research, Lead original research, Define technical direction, Own technical direction, Act as Principal Investigator, Drive research projects, Work hands-on, Publish high-quality research, Present results, Lead technical contributions, Serve as senior technical interface, Mentor researchers, Contribute to research culture, Contribute to technical excellence, Build research team, Lead research team", "teamCollaboration" : "Externally funded research programs; World-class national laboratories; Government agencies; Research institutions; Research and Engineering organization; Mathematicians; Physicists; Computer scientists; Hardware engineers; Software engineers; External partners; Government agencies; National labs; Research partners", "projectManagementSkills" : [ "Project management" ], "domainKnowledge" : "Quantum computing; Quantum error correction; Fault-tolerant architectures; Decoding algorithms; Noise characterization; System-level performance analysis; Quantum hardware; HPC research; Large-scale testbeds", "domainList" : [ "quantum-computing", "quantum-error-correction", "fault-tolerant-architectures", "decoding-algorithms", "noise-characterization", "system-level-performance-analysis", "quantum-hardware", "hpc-research", "large-scale-testbeds" ], "domainSpecificKnowledge" : [ "Quantum computing", "Quantum error correction", "Fault-tolerant architectures", "Decoding algorithms", "Noise characterization", "System-level performance analysis", "Quantum hardware", "HPC research", "Large-scale testbeds" ], "communicationSkills" : "Discuss complex ideas; Clear communication", "continuousLearning" : "Training budgets; Conference budgets", "innovationCreativity" : "Scientific inventiveness; New research directions", "problemSolvingSkills" : "Problem solving", "specialRequirements" : "US government clearance", "outcomesObjectives" : "Accelerate path to utility-scale quantum computing; Solve defining challenge of quantum computing", "qualificationsBasic" : "PhD in mathematics, physics, computer science, or related technical field, Equivalent professional experience, Experience as Principal Investigator, Engaging with different stakeholders, Track record of driving projects, Experience leading projects involving multiple people, Ability to work effectively independently, Ability to work effectively as part of a team, Must be able to obtain a US government clearance", "qualificationsPreferred" : "Experience leading collaborations with national labs, Experience leading collaborations with major research facilities, Experience leading collaborations with government-funded consortia, Contributed to large-scale scientific programs, Led large-scale scientific programs, Contributed to center-level research initiatives, Led center-level research initiatives, Deep expertise in QEC-relevant areas, Experience integrating quantum research with real hardware, Experience integrating HPC research with real hardware, Experience integrating quantum research with simulators, Experience integrating HPC research with simulators, Experience integrating quantum research with testbeds, Experience integrating HPC research with testbeds, Network across quantum computing research landscape, Track record of securing significant external funding, Mentored early-career researchers, Coached early-career researchers, Supervised early-career researchers, Mentored research engineers, Coached research engineers, Supervised research engineers", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "Principal Quantum Error Correction (QEC) Investigator Boston, MA, US | Full-time | Permanent | Hybrid Salary: $180,000 to $245,000 DOE The salary range for this role is broad, as we are able to consider varying levels of experience. Any offer made will carefully take into account level of experience (including relevant industry experience), transferable relevant skills and previous relevant achievements. Location note: For the right candidate, we are also able to consider this role on a fully remote basis from other parts of the US. In such cases, compensation will be adjusted accordingly, in line with the local market. About us Riverlane’s mission is to master quantum error correction (QEC) and unlock a new age of human progress. From advances in material and climate science, to complex chemistry simulation for new drug design, quantum computers will help humanity solve some of its most important challenges. But without QEC, the industry’s defining technical challenge, such breakthroughs can never be achieved. Riverlane is the world leader in QEC technology. QEC is a complex problem that requires a range of skills, talent and passion. Having raised more than $125M in funding to date to accelerate our cutting-edge R&D in quantum error correction (QEC), Riverlane partners with many of the world’s leading quantum hardware providers and government agencies to make fault-tolerant quantum computing a reality. We’re making remarkable progress and growing fast.  About the role As a Principal Investigator, QEC at Riverlane, you will lead some of the company’s highest-value, most strategically important research programs – collaborations with world-class national laboratories, government agencies, and major research institutions. These partnerships sit at the core of accelerating the path to utility-scale quantum computing, and require scientific inventiveness, technical depth, and the ability to shape the direction of ambitious, multi-stakeholder initiatives. You will operate across Riverlane’s highly collaborative Research and Engineering organization, working alongside mathematicians, physicists, computer scientists, and hardware and software engineers to push the frontier of quantum error correction. In this senior role, you will blend hands-on research with technical leadership, setting scientific direction, representing Riverlane to external partners at the highest technical level, and – when opportunities arise – building and mentoring a small research team. This is a role for someone who wants to have impact at scale: defining new research directions, influencing the national QEC landscape, and contributing directly to solving the defining challenge of quantum computing. What you will do As a Principal Investigator, QEC at Riverlane, your work will vary, but typical activities may include: Conceive, conduct, and lead original research in quantum error correction and related areas Define and own the technical direction for externally funded research programs Act as Principal Investigator with responsibility for technical delivery against agreed milestones Drive research projects from concept through execution, working hands-on where appropriate Publish high-quality research in leading journals and conferences, and present results at major venues Lead technical contributions to competitive funding proposals and oral evaluations Serve as Riverlane’s senior technical interface to government agencies, national labs, and research partners Mentor researchers and contribute to Riverlane’s research culture and technical excellence As programs grow and funding allows, there may be opportunities to build and lead a small research team What we need PhD in mathematics, physics, computer science, or a related technical field (or equivalent professional experience). Experience as Principal Investigator engaging with different stakeholders (ideally in the government sector). Track record of driving projects on time whilst meeting or exceeding expectations. Experience leading projects involving multiple people Ability to work effectively both independently, and as part of a team Strong written and oral communication skills, with the ability to discuss complex ideas with a variety of audiences in a clear way Must be able to obtain a US government clearance if required. Even better if You have experience leading collaborations with national labs, major research facilities, or government-funded consortia. You have contributed to or led large-scale, multi-year scientific programs or center-level research initiatives. You bring deep expertise in one or more QEC-relevant areas such as fault-tolerant architectures, decoding algorithms, noise characterization, or system-level performance analysis. You have experience integrating quantum or HPC research with real hardware systems, simulators, or large-scale testbeds. You have a strong network across the quantum computing research landscape and are comfortable representing an organization at senior technical forums. You have a track record of securing significant external funding through competitive grants or program-level proposals. You have mentored, coached, or supervised early-career researchers or research engineers, formally or informally. What can you expect from us A comprehensive benefits package that includes an annual bonus plan, private medical insurance, life insurance and 401K contributions Equity, so that our team can share in the long-term success of Riverlane  Generous paid time off, and enhanced family leave  A diverse work environment that brings together experts in many fields (including software and hardware development, quantum information theory, physics and math) and over 20 different nationalities   A learning environment that encourages individual, team and company growth and learning, including training and conference budgets How to apply Please upload a CV and cover letter by clicking 'Apply'. Your cover letter should explain why you are applying for the job and what skills and experience you can bring to the role. We review CVs as we receive them and interview as soon as we have applications that look like a good match. We do not use closing dates. So, please apply as soon as possible to avoid missing out on this role. If you have any queries, please contact jobs@riverlane.com. Everyone is welcome at Riverlane. We are an equal opportunity employer and encourage applications from eligible and suitably qualified candidates regardless of age, disability, ethnicity, gender, gender reassignment, religion or belief, sexual orientation, marital or civil partnership status, or pregnancy and maternity/paternity. Studies have shown that women tend to apply to jobs if they meet all or almost all of the requirements whereas men apply even if they meet only some of the requirements. If that sounds like you then please apply – we are happy to review your application and let you know if we think you might be a good fit. If you need any adjustments made to the application or selection process so you can do your best, please let us know. We will be happy to help. GDPR notice: Riverlane collects and processes personal data in accordance with applicable data protection laws. If you are a European Job Applicant see the privacy notice for further details. #LI-CA1", "summaryDescription" : "Principal Investigator, Quantum Error Correction at Riverlane. Skills: Quantum error correction, Research leadership. Conceive original research. Conduct original research", "postedDate" : "2026-06-13T20:35:20.500", "createdAt" : "2026-06-13T20:35:20.500", "lastUpdated" : "2026-06-15T07:46:50.364", "ingestTimestamp" : "2026-06-13T20:35:20.500", "mongoId" : "6a2c7ec074d8ee00a09537b7", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 180000, "salaryAnnualMax" : 245000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Fault-tolerant architectures", "Decoding algorithms", "Noise characterization", "System-level performance analysis", "Leadership", "Mentoring", "Quantum error correction", "Research leadership", "Scientific inventiveness", "Technical leadership", "Technical direction", "External research programs", "Funding proposals", "Oral evaluations", "Project management", "Quantum computing", "Quantum hardware", "HPC research", "Large-scale testbeds" ], "skillCount" : 19, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Executive", "dataQualityScore" : 1.0, "_score" : 438.89804, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2cda0c74d8ee00a0a4a9b5", "title" : "Measurement Analyst", "company" : "Nextdoor", "industry" : "Technology", "salary" : { "min" : 81000.0, "max" : 105000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "San Francisco, California, United States", "locations" : [ "San Francisco", "California", "United States", "Chicago", "Illinois", "United States", "New York", "New York", "United States" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-15T11:49:44.931", "fingerprint" : "add24fec937a4f8defdf567855dd6ba967680b17d2243b1d76feb19257d8095e", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://about.nextdoor.com/careers-list/?gh_jid=8003527", "externalId" : "8003527", "industryFunction" : { }, "structuredLocations" : [ { "city" : "San Francisco", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "37.7879363,-122.4075201" } ], "locationText" : "San Francisco, California, United States", "employmentType" : "FULL_TIME", "technicalSkills" : "SQL, Python, AI", "professionalSkills" : [ "Measurement strategy", "Client advising", "Data analysis", "Research studies", "Campaign analysis", "Best practices", "Playbook creation" ], "hardSkillsList" : [ "Measurement", "Data analysis", "Lift testing", "Incrementality testing", "Attribution", "Foot traffic", "Conversion lift" ], "hardSkills" : [ { "name" : "Measurement", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Lift testing", "level" : "intermediate" }, { "name" : "Incrementality testing", "level" : "intermediate" }, { "name" : "Attribution", "level" : "intermediate" }, { "name" : "Foot traffic", "level" : "intermediate" }, { "name" : "Conversion lift", "level" : "intermediate" } ], "majorSkills" : "Measurement, Data analysis, Client advising", "majorSkillsList" : [ "Measurement", "Data analysis", "Client advising" ], "coreResponsibilities" : "Lead measurement research studies, Manage research process, Deliver research results, Advocate measurement solutions, Implement measurement solutions, Present research results, Provide insights, Provide recommendations, Conduct in-depth analyses, Evaluate campaign tactics, Create best practices, Create playbooks, Leverage AI tools, Automate analysis tasks, Accelerate data summarization, Explore AI applications", "teamCollaboration" : "Internal sales teams; Account management teams; Sales teams; Product teams", "domainKnowledge" : "Measurement landscape; Lift testing; Incrementality testing; Attribution; Foot traffic; Conversion lift; Emerging trends", "domainList" : [ "measurement-landscape", "lift-testing", "incrementality-testing", "attribution", "foot-traffic", "conversion-lift", "emerging-trends" ], "domainSpecificKnowledge" : [ "Measurement landscape", "Lift testing", "Incrementality testing", "Attribution", "Foot traffic", "Conversion lift", "Emerging trends" ], "toolProficiency" : [ "Claude", "Gemini", "ChatGPT", "Glean" ], "communicationSkills" : "Present insights; Present recommendations; Client presentations", "problemSolvingSkills" : "Solve complex problems", "specialRequirements" : "In-person events, Team building exercises", "outcomesObjectives" : "Drive impactful results", "qualificationsBasic" : "Bachelor's or Master's degree, 0-2 years experience, SQL proficiency, Python proficiency", "qualificationsPreferred" : "PhD preferred, GCP Professional Data Engineer, AWS Data Analytics, Databricks Certified, Dbt Certified", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "#TeamNextdoor Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 350,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com. Meet Your Future Neighbors As a Measurement Analyst at Nextdoor, you’ll work at the forefront of strategizing and recommending measurement strategies for our advertisers. As experts in measurement and data, we provide essential technical support to our sales team and deliver value to our clients. Our sales team will count on you to be a trusted adviser to clients while working with them to advise clients on measurement strategies using a mix of first and third party measurement solutions. You will solve complex clients problems and drive impactful results. At Nextdoor, we operate in an AI-first environment and expect every team member to actively use AI tools as part of their workflow. We aren't looking for prompt engineers; we’re looking for people who use tools like Claude, Gemini, ChatGPT, and Glean to challenge their own thinking and take full ownership of AI-assisted outputs. We also offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The hiring team will go over these expectations with you if you are being considered for a role near one of our offices in San Francisco, Los Angeles, Chicago, Dallas, New York, and London. The Impact You’ll Make For a specific set of advertisers, you will lead measurement research studies, managing the entire process from setup through to delivering results Be an advocate for Nextdoor’s measurement solutions within internal sales and account management teams, ensuring their effective implementation in client campaigns Lead the presentation of measurement research results, including insights and recommendations, to clients Conduct in-depth analyses to evaluate the effectiveness of various campaign tactics and create actionable best practices and playbooks Participate in-person Nextdoor events, trainings, off-sites, volunteer days, and other team building exercises Build in-person relationships with team members and contribute to the KIND culture that Nextdoor values Leverage AI tools to enhance day-to-day measurement workflows including automating repetitive analysis tasks, accelerating data summarization and continuously exploring new AI applications relevant to the measurement and analytics space What You’ll Bring To The Team Bachelor’s or Master’s degree in a quantitative field such as statistics, business analytics, or marketing 0-2 years of experience in digital analytics, marketing analytics, media measurement or similar experience at an advertiser, media platform, measurement provider, or media advertising agency An understanding of the measurement landscape, including lift and incrementality testing, attribution, foot traffic and conversion lift, as well as emerging trends in measurement Demonstrated client service background, you thrive in externally facing conversations, working with clients to understand their campaign goals and accordingly recommend measurement opportunities A strong track record partnering across sales, account management and product teams to drive towards a common outcome Clear and concise communication; comfortable with presenting campaign and measurement insights and recommendations to senior stakeholders Ability to handle multiple projects simultaneously in a fast-paced, high-growth environment Comfortable extracting and analyzing large datasets using SQL and or Python A strong passion for Nextdoor's mission Rewards Compensation, benefits, perks, and recognition programs at Nextdoor come together to create one overall rewards package. The starting salary for this role is expected to range from $81,000 - $105,000 on an annualized basis, or potentially greater in the event that your 'level' of proficiency exceeds the level expected for the role. The salary range will be determined by the candidate’s geographic location. We expect to award a meaningful equity grant for this role. With quarterly vesting, your first vest date will take place within 3 months of your start date. When it comes to benefits, we have you covered! Nextdoor employees can choose between a variety of health plans, including a 100% covered employee only plan option, and we also provide a OneMedical membership for concierge care. At Nextdoor, we empower our employees to build stronger local communities. To create a platform where all feel welcome, we want our workforce to reflect the diversity of the neighbors we serve. We encourage everyone interested in our mission to apply. We do not discriminate on the basis of race, gender, religion, sexual orientation, age, or any other trait that unfairly targets a group of people. In accordance with the San Francisco Fair Chance Ordinance, we always consider qualified applicants with arrest and conviction records. For information about our collection and use of applicants’ personal information, please see Nextdoor's Personnel Privacy Notice, found here.", "summaryDescription" : "Measurement Analyst at Nextdoor. Skills: Measurement, Data analysis, Client advising. Lead measurement research studies. Manage research process", "postedDate" : "2026-06-13T22:27:41.763", "createdAt" : "2026-06-13T22:27:41.763", "lastUpdated" : "2026-06-15T11:49:44.931", "ingestTimestamp" : "2026-06-13T22:27:41.763", "mongoId" : "6a2cda0c74d8ee00a0a4a9b5", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 81000, "salaryAnnualMax" : 105000, "salaryBand" : "75k-100k", "hasSalary" : true, "allSkills" : [ "Measurement", "Data analysis", "Lift testing", "Incrementality testing", "Attribution", "Foot traffic", "Conversion lift", "Client advising", "Measurement strategy", "Research studies", "Campaign analysis", "Best practices", "Playbook creation", "Measurement landscape", "Emerging trends", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "Claude", "Gemini", "ChatGPT", "Glean" ], "skillCount" : 23, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Junior", "dataQualityScore" : 0.8888889, "_score" : 435.61322, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "69cf3f072beec4dd3d93421e", "title" : "Quantitative UX Researcher", "company" : "Amazon Web Services, Inc.", "industry" : "Design, Cloud Computing", "salary" : { "min" : 130000.0, "max" : 176000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Seattle, Washington, USA", "locations" : [ "Seattle, Washington, USA" ], "timestamp" : "2026-06-15T04:25:29.969", "fingerprint" : "706e33469aeed1131c6161b0d169bd291f6fd5011c7161ad08e35ac25b2730c5", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/10381814/apply", "externalId" : "82c04ed8-855f-4683-87ae-79147868057f", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Seattle", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6038321,-122.3300620" } ], "locationText" : "Seattle, Washington, United States", "employmentType" : "FULL_TIME", "technicalSkills" : "Python, R, AI, ML", "professionalSkills" : [ "Behavioral analysis", "Causal inference", "Product direction", "Product decisions", "Product performance", "Customer needs", "Customer value", "AI-powered experiences" ], "hardSkillsList" : [ "Experimentation", "Analytics", "Quantitative research", "Mixed-methods research", "Study design", "Hypothesis definition", "Success metrics", "Data analysis", "Statistical analysis" ], "hardSkills" : [ { "name" : "Experimentation", "level" : "intermediate" }, { "name" : "Analytics", "level" : "intermediate" }, { "name" : "Quantitative research", "level" : "intermediate" }, { "name" : "Mixed-methods research", "level" : "intermediate" }, { "name" : "Study design", "level" : "intermediate" }, { "name" : "Hypothesis definition", "level" : "intermediate" }, { "name" : "Success metrics", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Statistical analysis", "level" : "intermediate" } ], "majorSkills" : "Quantitative UX Research, Applied AI, Experimentation, Causal inference", "majorSkillsList" : [ "Quantitative UX Research", "Applied AI", "Experimentation", "Causal inference" ], "coreResponsibilities" : "Lead quantitative research, Turn product questions into hypotheses, Define success metrics, Design studies, Generate actionable insights, Evaluate new ideas, Improve existing experiences, Make product decisions, Lead quantitative research for AI products, Own studies end to end, Frame research questions, Define hypotheses, Select research methods, Identify measures, Analyze results, Communicate recommendations, Design experiments, Run experiments, Design surveys, Run surveys, Conduct behavioral analyses, Define success metrics for AI experiences, Track success metrics, Combine findings across research, Combine findings with product usage, Combine findings with customer feedback, Generate clear insights, Generate practical product recommendations, Partner with product, Partner with design, Partner with engineering, Support build test learn approach, Inform decisions throughout product lifecycle", "teamCollaboration" : "Product teams; Design teams; Engineering teams", "domainKnowledge" : "AI-native applications; AI-powered experiences; AI innovation", "domainList" : [ "ai-native-applications", "ai-powered-experiences", "ai-innovation" ], "domainSpecificKnowledge" : [ "AI-native applications", "AI-powered experiences", "AI innovation" ], "problemSolvingSkills" : "Data-driven decision making", "qualificationsBasic" : "3+ years User Research, Master's degree in quantitative field, Experience with data analytics, Experience with AI/ML technologies, Knowledge of quantitative data analysis, Experience with Python or R", "qualificationsPreferred" : "Experience communicating research findings, Experience developing V1 products, Experience building scalable programs", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "We are seeking a Quantitative UX Researcher who is excited to help shape the future of AI-native business applications. This is an opportunity to influence product direction by helping teams understand how customers interact with AI-powered experiences and what drives adoption, trust, usability, and customer value. In this role, you will lead quantitative research that helps teams build, test, and learn faster. You will turn product questions into clear hypotheses, success metrics, well-designed studies, and actionable insights. Your work will help teams evaluate new ideas, improve existing experiences, and make better product decisions. This is a quant-first role with mixed-methods responsibilities as needed. We are looking for a researcher with strong skills in experimentation, analytics, behavioral analysis, and causal inference. You should be comfortable working in ambiguous, early-stage spaces and helping teams define how success should be measured for new AI-powered products. You will identify meaningful behavioral and attitudinal signals, measure product performance, and recommend improvements based on the evidence. Key job responsibilities - Lead quantitative and mixed-methods research for AI-powered products, including early-stage concepts and evolving customer experiences. - Own studies from end to end, including framing research questions, defining hypotheses, selecting methods, identifying measures, analyzing results, and communicating recommendations. - Design and run experiments, surveys, and behavioral analyses that help teams understand customer needs, product performance, and opportunities for improvement. - Define and track success metrics related to adoption, trust, usability, comprehension, and customer value in AI-powered experiences. - Combine findings across research, product usage, and customer feedback to generate clear insights and practical product recommendations. - Partner closely with product, design, and engineering to support a build, test, learn approach, where evidence informs decisions throughout the product lifecycle. About the team AWS Applied AI Solutions is an organization with ambitions to be a leading provider of business applications, leveraging Amazon's unique experience and expertise, used by millions of companies worldwide to manage day-to-day operations. Our mission is to accelerate our customers' businesses by delivering intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. The AWS Applied AI Solutions team is at the forefront of AI innovation, designing and building the next generation of intelligent business applications. We work closely with global Product, Engineering, Science, Marketing, and Business Development teams to deliver compelling AI-powered experiences that transform how businesses operate. Our research team plays a critical role in ensuring these AI solutions are not just technically advanced, but truly meet customer needs and drive meaningful customer outcomes. Basic Qualifications: - 3+ years of proven success leading User Research projects with demonstrated impact experience - Experience (end to end) with all aspects of research (study design, recruiting, moderation, analysis, reporting) - Have a portfolio demonstrating past work experience and deliverables (e.g., study plans, reports, personas) - Master's degree in a quantitative field - Experience working with data and leveraging analytics to make decisions - Experience with AI/ML technologies - Knowledge of quantitative data analysis and statistics - Experience with Python or R Preferred Qualifications: - Experience communicating research findings and analysis in both written and spoken channels - Experience developing and launching V1 products - Experience building scalable programs and repeatable scalable processes, levering various tools and methods to create scale and efficiency Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, NY, New York - 143,100.00 - 193,600.00 USD annually USA, WA, Seattle - 130,100.00 - 176,000.00 USD annually", "summaryDescription" : "Quantitative UX Researcher at Amazon Web Services, Inc.. Skills: Quantitative UX Research, Applied AI, Experimentation, Causal inference. Lead quantitative research. Turn product questions into hypotheses", "postedDate" : "2026-06-13T04:47:53.913", "createdAt" : "2026-06-13T04:47:53.913", "lastUpdated" : "2026-06-15T04:25:29.969", "ingestTimestamp" : "2026-06-13T04:47:53.913", "mongoId" : "69cf3f072beec4dd3d93421e", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/10381814/apply", "salaryAnnualMin" : 130000, "salaryAnnualMax" : 176000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Experimentation", "Analytics", "Quantitative research", "Mixed-methods research", "Study design", "Hypothesis definition", "Success metrics", "Data analysis", "Statistical analysis", "Quantitative UX Research", "Applied AI", "Causal inference", "Behavioral analysis", "Product direction", "Product decisions", "Product performance", "Customer needs", "Customer value", "AI-powered experiences", "AI-native applications", "AI innovation" ], "skillCount" : 21, "jobCategory" : "design", "dataQualityScore" : 0.8888889, "_score" : 433.91803, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology" }, { "id" : "6a2c5e8d74d8ee00a08e4da9", "title" : "Measurement Lead", "company" : "Brandtech+", "salary" : { "min" : 2500000.0, "max" : 4500000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Lead Measurement role in the Marketing industry, adjusted for a remote position in India." }, "location" : "BTG+", "locations" : [ "BTG+" ], "timestamp" : "2026-06-15T00:28:09.903", "fingerprint" : "094024f3916f2150eb92a7084d9e0abf67f2206191a2185e2db4d5deda186410", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/brandtechplus/jobs/8000033", "externalId" : "8000033", "structuredLocations" : [ { "workMode" : "remote" } ], "locationText" : "", "experienceMinYears" : 8, "experienceMaxYears" : 15, "experienceLevel" : "Lead", "technicalSkills" : "SQL, Python, R, Scala, Spark, dbt, Tableau, Power BI, Looker Studio, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, dbt Cloud, Delta Lake, scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, GCP, Azure", "professionalSkills" : [ "Data governance", "Performance analysis", "Operational efficiency", "Commercial insight", "Client reporting" ], "hardSkillsList" : [ "Statistical analysis", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference", "Data validation", "Quality assurance", "Forecasting", "Planning" ], "softSkillsList" : [ "Leadership", "Critical thinking", "Adaptability", "Negotiation", "Mentoring" ], "hardSkills" : [ { "name" : "Statistical analysis", "level" : "intermediate" }, { "name" : "Regression", "level" : "intermediate" }, { "name" : "Classification", "level" : "intermediate" }, { "name" : "Clustering", "level" : "intermediate" }, { "name" : "Time-series analysis", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" }, { "name" : "Data validation", "level" : "intermediate" }, { "name" : "Quality assurance", "level" : "intermediate" }, { "name" : "Forecasting", "level" : "intermediate" }, { "name" : "Planning", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Critical thinking" }, { "name" : "Adaptability" }, { "name" : "Negotiation" }, { "name" : "Mentoring" } ], "majorSkills" : "Data governance, Performance reporting, Stakeholder management, Data analysis", "majorSkillsList" : [ "Data governance", "Performance reporting", "Stakeholder management", "Data analysis" ], "coreResponsibilities" : "Support development of reporting frameworks, Establish consistent tracking approaches, Standardise reporting structures, Define KPI definitions, Define data taxonomies, Ensure reporting aligns to client objectives, Ensure reporting aligns to business priorities, Ensure reporting aligns to operational requirements, Own data integrity, Maintain data integrity, Implement data validation processes, Implement quality assurance processes, Implement reporting accuracy processes, Identify reporting inconsistencies, Identify reporting gaps, Identify reporting risks, Resolve reporting issues, Promote data management best practices, Promote reporting governance best practices, Build regular reporting outputs, Translate complex datasets into insight, Support governance forums, Support performance reviews, Support client reporting, Analyse delivery trends, Analyse utilisation trends, Analyse efficiency trends, Analyse financial performance trends, Improve visibility across workflows, Improve visibility across resource planning, Improve visibility across performance tracking, Support forecasting activities, Support planning activities, Support performance analysis activities, Identify operational inefficiencies, Identify optimisation opportunities, Contribute to scalable reporting solutions, Contribute to automated workflows, Support integration across reporting tools, Support integration across delivery systems, Support integration across finance platforms, Support integration across workflow trackers, Improve reporting accessibility, Improve reporting automation, Improve reporting usability, Streamline reporting processes, Reduce manual effort, Encourage consistent adoption of measurement frameworks, Encourage consistent adoption of reporting best practices, Partner with internal stakeholders, Understand reporting needs, Understand reporting priorities, Support client-facing reporting requirements, Present clear data, Present accurate data, Present transparent data, Shape performance narratives, Shape reporting materials for governance meetings, Shape reporting materials for business reviews, Build working relationships across teams, Ensure alignment across teams, Ensure consistency across teams", "teamCollaboration" : "Global teams; Regional teams; Delivery teams; Operations teams; Finance teams; Strategy teams; Internal stakeholders; Client-facing reporting", "domainKnowledge" : "Marketing operations; Agency reporting; Client value demonstration", "domainList" : [ "marketing-operations", "agency-reporting", "client-value-demonstration" ], "domainSpecificKnowledge" : [ "Marketing operations", "Agency reporting", "Client value demonstration" ], "toolProficiency" : [ "Power BI", "Tableau", "Looker Studio" ], "communicationSkills" : "Clear communication; Concise communication; Commercially relevant insight; Performance narratives; Data presentation", "continuousLearning" : "Always learning and listening", "innovationCreativity" : "Leveraging cutting-edge AI technology; Enhance efficiency; Spark creativity; Drive insightful decision-making; Produce innovative results", "problemSolvingSkills" : "Analytical capability; Problem-solving skills; Translate complexity; Practical recommendations", "outcomesObjectives" : "Demonstrate value to clients; Support effective decision-making", "qualificationsBasic" : "5–8+ years’ experience in reporting, analytics, operations, or performance-focused roles, Advanced Excel skills, Experience using reporting and visualisation tools", "qualificationsPreferred" : "PhD preferred, Specific ML framework experience, Cloud platform certs", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Brandtech+ (formerly known as OLIVER+) is a global team of creative thinkers, tech-savvy trendsetters, and production pros specialising in film, CGI, automation, AI, motion design, and digital/print content. We partner with over 300 clients in 40+ countries and counting. Our focus is to connect clients with high-quality solutions, talent and ambitious opportunities worldwide.  As a part of The Brandtech Group, we're at the forefront of leveraging cutting-edge AI technology to revolutionise how we create and deliver work. Our AI solutions enhance efficiency, spark creativity, and drive insightful decision-making, empowering our teams to produce innovative and impactful results. Role: Measurement Lead Location: Remote working until further notice ABOUT THE ROLE: Brandtech+ is evolving how data is structured, governed, and utilised across global client accounts. The Measurement Lead plays a key role in shaping how delivery, operational, financial, and performance data are captured, connected, interpreted, and communicated across The Mix. This role is responsible for driving consistency, accuracy, and transparency across reporting and measurement frameworks, ensuring stakeholders have access to reliable, actionable insights that support effective decision-making and demonstrate value to clients. Working closely with global and regional teams across delivery, operations, finance, and strategy, the Measurement Lead will support the development of scalable reporting structures, robust data governance processes, and integrated performance views across projects, people, finance, and operational metrics. The role is suited to someone who combines strong analytical capability with operational understanding and excellent stakeholder management skills. The successful candidate will be comfortable working across multiple data sources and business functions, translating complexity into clear reporting, meaningful insight, and practical recommendations. This is a hands-on role within a fast-moving global environment, requiring a proactive and detail-oriented individual who can balance strategic thinking with day-to-day execution and continuous improvement. WHAT YOU WILL BE DOING: Measurement & Reporting Frameworks Support the development and ongoing evolution of reporting and measurement frameworks across The Mix. Establish consistent approaches to tracking delivery, operational, financial, and performance metrics. Help standardise reporting structures, KPI definitions, and data taxonomies across markets and teams. Ensure reporting outputs align to client objectives, business priorities, and operational requirements. Data Governance & Quality Control Own and maintain data integrity across reporting inputs and outputs. Develop and implement processes for data validation, quality assurance, and reporting accuracy. Identify inconsistencies, gaps, and risks within reporting structures and work with stakeholders to resolve them. Promote best practice approaches to data management and reporting governance across teams. Performance Reporting & Insight Build and maintain regular reporting outputs for global and regional stakeholders. Translate complex datasets into clear, concise, and commercially relevant insight. Support governance forums, performance reviews, and client reporting through accurate and meaningful performance narratives. Analyse trends and patterns across delivery, utilisation, efficiency, and financial performance metrics. Operational & Commercial Support Work closely with delivery, operations, and finance teams to improve visibility across workflows, resource planning, and performance tracking. Support forecasting, planning, and performance analysis activities through reliable reporting and structured insight. Assist in identifying operational inefficiencies and opportunities for optimisation through data analysis. Contribute to the development of scalable reporting solutions and automated workflows where appropriate. Tools, Systems & Process Improvement Support integration and alignment across reporting tools, delivery systems, finance platforms, and workflow trackers. Help improve reporting accessibility, automation, and usability across teams. Partner with operational and technology stakeholders to streamline reporting processes and reduce manual effort. Encourage consistent adoption of measurement frameworks and reporting best practices globally. Stakeholder & Client Collaboration Partner with internal stakeholders across delivery, strategy, finance, and operations to understand reporting needs and priorities. Support client-facing reporting requirements with clear, accurate, and transparent data presentation. Help shape performance narratives and reporting materials for governance meetings and business reviews. Build strong working relationships across global and regional teams to ensure alignment and consistency. WHAT YOU WILL NEED TO BE GREAT AT THIS ROLE: 5–8+ years’ experience in reporting, analytics, operations, or performance-focused roles within agencies, marketing operations, or in-house environments. Strong analytical and problem-solving skills, with the ability to interpret and communicate complex information clearly. Experience working with performance reporting, operational data, financial metrics, and KPI tracking. Advanced Excel skills and confidence working with large or complex datasets. Experience using reporting and visualisation tools such as Power BI, Tableau, Looker Studio, or equivalent platforms. Strong organisational skills with high attention to detail and accuracy. Ability to manage multiple priorities and stakeholders within fast-paced environments. Excellent communication and stakeholder management skills. A collaborative and proactive approach, with a strong focus on continuous improvement. Req ID - 17490 #LI-SJ1 #LI-REMOTE #LI-Senior #BTG+ Our values shape everything we do: Be Ambitious to succeed  Be Imaginative to push the boundaries of what’s possible  Be Inspirational to do groundbreaking work  Be always learning and listening to understand  Be Results-focused  to exceed expectations  Be actively pro-inclusive and anti-racist across our community, clients and creations  Brandtech+, a part of the Brandtech Group, is an equal opportunity employer committed to creating an inclusive working environment where all employees are encouraged to reach their full potential, and individual differences are valued and respected. All applicants shall be considered for employment without regard to race, ethnicity, religion, gender, sexual orientation, gender identity, age, neurodivergence, disability status, or any other characteristic protected by local laws.  Brandtech+ has set ambitious environmental goals around sustainability, with science-based emissions reduction targets. Collectively, we work towards our mission, embedding sustainability into every department and through every stage of the project lifecycle.'", "summaryDescription" : "Measurement Lead at Brandtech+. Skills: Data governance, Performance reporting, Stakeholder management, Data analysis. Support development of reporting frameworks. Establish consistent tracking approaches", "postedDate" : "2026-06-12T22:01:39.804", "createdAt" : "2026-06-12T22:01:39.804", "lastUpdated" : "2026-06-15T00:28:09.903", "ingestTimestamp" : "2026-06-12T22:01:39.804", "mongoId" : "6a2c5e8d74d8ee00a08e4da9", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Statistical analysis", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference", "Data validation", "Quality assurance", "Forecasting", "Planning", "Leadership", "Critical thinking", "Adaptability", "Negotiation", "Mentoring", "Data governance", "Performance reporting", "Stakeholder management", "Data analysis", "Performance analysis", "Operational efficiency", "Commercial insight", "Client reporting", "Marketing operations", "Agency reporting", "Client value demonstration", "Power BI", "Tableau", "Looker Studio" ], "skillCount" : 30, "jobCategory" : "other", "jobSubcategory" : "analytics-", "dataQualityScore" : 0.8888889, "_score" : 433.90744, "daysOld" : 2, "hasLocation" : true, "hasGeo" : false }, { "id" : "6a2c7c2b74d8ee00a094c83a", "title" : "Senior Quantitative Researcher - Macro", "company" : "Man Group", "industry" : "Banking", "salary" : { "min" : 150000.0, "max" : 250000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Quantitative Researcher in London, UK, adjusted for the financial services industry and a large company size." }, "location" : "London", "locations" : [ "London" ], "timestamp" : "2026-06-15T03:20:54.912", "fingerprint" : "ba85dc9218df5216bb9256c3e9d931b95402fb9d10c51323ac42edb4bdbdbbde", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.eu.greenhouse.io/mangroup/jobs/4724414101", "externalId" : "4724414101", "industryFunction" : { }, "structuredLocations" : [ { "city" : "London", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "51.5074456,-0.1277653" } ], "locationText" : "London, United Kingdom", "experienceMinYears" : 4, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, SQL", "professionalSkills" : [ "Alpha signal research", "Live trading", "Predictor design", "Portfolio construction", "Risk analysis", "Transaction cost analysis", "Data handling" ], "hardSkillsList" : [ "Quantitative research", "Systematic trading", "Futures trading", "FX trading", "Data analysis" ], "softSkillsList" : [ "Intellectual honesty", "Mentoring", "Analytic approach", "Self-organised", "Interpersonal", "Confident communicator" ], "hardSkills" : [ { "name" : "Quantitative research", "level" : "intermediate" }, { "name" : "Systematic trading", "level" : "intermediate" }, { "name" : "Futures trading", "level" : "intermediate" }, { "name" : "FX trading", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Intellectual honesty" }, { "name" : "Mentoring" }, { "name" : "Analytic approach" }, { "name" : "Self-organised" }, { "name" : "Interpersonal" }, { "name" : "Confident communicator" } ], "majorSkills" : "Quantitative research, Systematic trading, Futures, FX", "majorSkillsList" : [ "Quantitative research", "Systematic trading", "Futures", "FX" ], "coreResponsibilities" : "Research alpha signals, Live trade alpha signals, Design predictors, Analyze predictors, Construct portfolios, Analyze risk, Mitigate transaction costs, Handle large data sets", "teamCollaboration" : "Quantitative researchers; Technologists; Traders; Senior stakeholders", "domainKnowledge" : "Financial markets; Futures; FX", "domainList" : [ "financial-markets", "futures", "fx" ], "domainSpecificKnowledge" : [ "Financial markets", "Futures", "FX" ], "toolProficiency" : [ "Python scientific stack", "Bloomberg Terminal", "Reuters Eikon", "FactSet" ], "communicationSkills" : "Argue concisely; Deal with conflicting views", "problemSolvingSkills" : "Problem solving", "qualificationsBasic" : "4+ years research experience, 4+ years live trading experience, Degree with high mathematical content, Degree with high statistical content, Degree with high computing content", "qualificationsPreferred" : "Experience with intraday predictor design, Experience with monthly predictor design, Experience with portfolio construction, Experience with risk analysis, Understanding of transaction costs, Understanding of mitigation strategies, Ability to mentor junior researchers", "workSiteFlexibility" : "Flexible", "rawDescription" : "About Man Group Man Group is a global alternative investment management firm focused on pursuing outperformance for sophisticated clients via our Systematic, Discretionary and Solutions offerings. Powered by talent and advanced technology, our single and multi-manager investment strategies are underpinned by deep research and span public and private markets, across all major asset classes, with a significant focus on alternatives. Man Group takes a partnership approach to working with clients, establishing deep connections and creating tailored solutions to meet their investment goals and those of the millions of retirees and savers they represent. Headquartered in London, we manage $227.6 billion* and operate across multiple offices globally. Man Group plc is listed on the London Stock Exchange under the ticker EMG.LN and is a constituent of the FTSE 250 Index. Further information can be found at www.man.com * As at 31 December 2025 About Man AHL: Man AHL employs diversified quantitative techniques to offer a range of strategies which encompass traditional momentum, non-traditional momentum, multi-strategy and sector-based approaches. Man AHL’s strategies are primarily alternative and seek to gain potential predictive, alpha-generating insights through rigorous analysis of large data sets. Man AHL is a specialised engine, applying scientific rigour and advanced technology and execution to a diverse range of data to build systematic investment strategies, trading continuously over hundreds of global markets. The team of 150 investment professionals, including 110 researchers, is comprised of scientists, technologists and finance practitioners, driven by curiosity and intellectual honesty, and a passion for solving the complex problems presented by financial markets. The engine leverages Man Group’s unique collaboration with the University of Oxford, the Oxford-Man Institute of Quantitative Finance (OMI). The OMI conducts field-leading academic research into machine learning and data analytics, which can be applied to quantitative investing. Founded in 1987, Man AHL’s funds under management were $63.8 billion at 31 March 2024. Further information can be found at www.man.com/ahl. The Team: AHL Macro is the team responsible for Macro strategies. The team systematically trades liquid futures and FX at different frequencies, with holding periods ranging from monthly to intraday. Technology and Business Skills: 4+ years of experience researching and live trading alpha signals for futures and FX Experience with intraday > monthly predictor design and analysis Experience with portfolio construction, risk analysis Strong understanding of transaction costs, and mitigation strategies Strong coding skills and experience of handling large data sets. We use Python and its scientific stack for both research and live trading Personal Attributes: Strong academic record and a degree with high mathematical, statistical, and computing content e.g., Mathematics, Computer Science, Engineering, Economics or Physics from a leading university Hands-on attitude; willing to get involved with technology and projects across the firm Intellectually robust with a keenly analytic approach to problem solving Self-organised with the ability to effectively manage time across multiple projects and with contending business demands and priorities Strong interpersonal skills; able to build and maintain a close working relationship with quantitative researchers, technologist, traders and senior business stakeholders alike. Ability to mentor junior researchers Confident communicator: able to argue a point concisely and deal positively with conflicting views Working Here: AHL fosters a performance driven, meritocratic culture with a small company, no-attitude feel. It is flat structured, open, transparent, and collaborative, offering ample opportunity to grow and have enormous impact on what we do. We are actively engaged with the broader research and academic community, as well as renowned industry contributors. Inclusion, Work-Life Balance and Benefits at Man Group You'll thrive in our working environment that champions equality of opportunity. Your unique perspective will contribute to our success, joining a workplace where inclusion is fundamental and deeply embedded in our culture and values. Through our external and internal initiatives, partnerships and programmes, you'll find opportunities to grow, develop your talents, and help foster an inclusive environment for all across our firm and industry. Learn more at www.man.com/diversity. You'll have opportunities to make a difference through our charitable and global initiatives, while advancing your career through professional development, and with flexible working arrangements available too. Like all our people, you'll receive two annual 'Mankind' days of paid leave for community volunteering. Our comprehensive benefits package includes competitive holiday entitlements, pension/401k, life and long-term disability coverage, group sick pay, enhanced parental leave and long-service leave. Depending on your location, you may also enjoy additional benefits such as private medical coverage, discounted gym membership options and pet insurance. Equal Employment Opportunity Policy Man Group provides equal employment opportunities to all applicants and all employees without regard to race, color, creed, national origin, ancestry, religion, disability, sex, gender identity and expression, marital status, sexual orientation, military or veteran status, age or any other legally protected category or status in accordance with applicable federal, state and local laws. Man Group is a Disability Confident Committed employer; if you require help or information on reasonable adjustments as you apply for roles with us, please contact TalentAcquisition@man.com.", "summaryDescription" : "Senior Quantitative Researcher - Macro at Man Group. Skills: Quantitative research, Systematic trading, Futures, FX. Research alpha signals. Live trade alpha signals", "postedDate" : "2026-06-13T21:53:56.911", "createdAt" : "2026-06-13T21:53:56.911", "lastUpdated" : "2026-06-15T03:20:54.912", "ingestTimestamp" : "2026-06-13T21:53:56.911", "mongoId" : "6a2c7c2b74d8ee00a094c83a", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "150k-200k", "hasSalary" : false, "allSkills" : [ "Quantitative research", "Systematic trading", "Futures trading", "FX trading", "Data analysis", "Intellectual honesty", "Mentoring", "Analytic approach", "Self-organised", "Interpersonal", "Confident communicator", "Futures", "FX", "Alpha signal research", "Live trading", "Predictor design", "Portfolio construction", "Risk analysis", "Transaction cost analysis", "Data handling", "Financial markets", "Python scientific stack", "Bloomberg Terminal", "Reuters Eikon", "FactSet" ], "skillCount" : 25, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "_score" : 433.90192, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Financial Services", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2ca0a374d8ee00a09a2cd8", "title" : "Senior Quantitative Risk Strategist", "company" : "Binance. US", "industry" : "Product", "salary" : { "min" : 180000.0, "max" : 280000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Quantitative Risk Strategist in the US FinTech industry, adjusted for seniority and company size." }, "location" : "U.S. ", "locations" : [ "U.S. " ], "timestamp" : "2026-06-15T03:20:23.949", "fingerprint" : "dffe190734707ce386d9658fa79f71f6cb37aca2539a9b2a2158bfe26b2b2531", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/binance.us/2deb43d1-ea00-4cdc-910a-b100b604895f/application", "externalId" : "2deb43d1-ea00-4cdc-910a-b100b604895f", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, R, MATLAB, SQL, Machine learning", "professionalSkills" : [ "Risk analytics", "Fraud science", "Payments risk", "Risk modeling", "Data analysis", "Decision making" ], "hardSkillsList" : [ "Predictive modeling", "Quantitative analysis", "Statistical methods", "Anomaly detection", "Data analysis", "Risk assessment", "Model validation", "Model governance" ], "hardSkills" : [ { "name" : "Predictive modeling", "level" : "intermediate" }, { "name" : "Quantitative analysis", "level" : "intermediate" }, { "name" : "Statistical methods", "level" : "intermediate" }, { "name" : "Anomaly detection", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Risk assessment", "level" : "intermediate" }, { "name" : "Model validation", "level" : "intermediate" }, { "name" : "Model governance", "level" : "intermediate" } ], "majorSkills" : "Quantitative risk modeling, Payments risk strategy, Risk decisioning, Fraud prevention", "majorSkillsList" : [ "Quantitative risk modeling", "Payments risk strategy", "Risk decisioning", "Fraud prevention" ], "coreResponsibilities" : "Design predictive risk models, Develop predictive risk models, Deploy predictive risk models, Improve predictive risk models, Build customer-level models, Build transaction-level models, Build portfolio-level models, Develop risk segmentation frameworks, Apply statistical methods, Apply machine learning techniques, Apply anomaly detection, Apply large-scale data analysis, Quantify risk across payment rails, Monitor risk across payment rails, Develop forecasting methodologies, Establish key risk indicators, Establish operational thresholds, Establish portfolio health metrics, Establish executive reporting frameworks, Evaluate impact of new products, Evaluate impact of payment methods, Evaluate impact of customer segments, Evaluate impact of growth initiatives, Embed model-driven decisioning, Design risk rules, Test risk rules, Optimize risk rules, Design risk controls, Test risk controls, Optimize risk controls, Design decision engines, Test decision engines, Optimize decision engines, Design transaction monitoring systems, Test transaction monitoring systems, Optimize transaction monitoring systems, Lead champion/challenger testing, Lead experimentation frameworks, Measure effectiveness of risk controls, Drive continuous improvement, Quantify tradeoffs, Support data-driven decision making, Conduct deep-dive investigations, Identify root causes, Recommend corrective actions, Support model governance, Support model validation, Support model audit, Support regulatory review, Establish model performance monitoring, Establish model calibration, Establish backtesting processes, Serve as trusted advisor", "teamCollaboration" : "Partner with Product; Partner with Engineering; Partner with Risk; Partner with Compliance; Partner with Data; Partner with Operations", "domainKnowledge" : "Financial services; Fintech; Cryptocurrency; Payments risk; Fraud; ACH; Card payments; Transaction risk; Predictive modeling; Risk analytics; Financial crime risk", "domainList" : [ "financial-services", "fintech", "cryptocurrency", "payments-risk", "fraud", "ach", "card-payments", "transaction-risk", "predictive-modeling", "risk-analytics", "financial-crime-risk" ], "domainSpecificKnowledge" : [ "Financial services", "Fintech", "Cryptocurrency", "Payments risk", "Fraud", "ACH", "Card payments", "Transaction risk", "Predictive modeling", "Risk analytics", "Financial crime risk" ], "toolProficiency" : [ "Bloomberg Terminal", "Reuters Eikon", "FactSet" ], "documentationSkills" : "Comprehensive documentation", "problemSolvingSkills" : "Root cause analysis", "qualificationsBasic" : "8+ years quantitative risk analytics, 8+ years fraud science, 8+ years payments risk, 8+ years machine learning, 8+ years data science, 8+ years risk modeling", "qualificationsPreferred" : "Advanced degree in Statistics, Advanced degree in Mathematics, Advanced degree in Economics, Advanced degree in Finance, Advanced degree in Computer Science, Advanced degree in Physics, Advanced degree in Operations Research, Advanced degree in Data Science", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "About Binance.US: Binance.US is America’s home to buy, trade, and earn digital assets. As a licensed and regulated U.S. crypto platform, we provide secure, reliable access to more than 190 of the world’s most popular cryptocurrencies, all with some of the lowest fees in the industry. We’re a remote-first team of innovators building the bridge between traditional finance and Web3, helping bring financial freedom within reach for all. To learn more, visit www.binance.us http://www.binance.us. All roles supporting Binance.US http://Binance.US are employed via BAM Management US Holdings Inc. or BAM Management Canada Holdings Inc. About This Role: The Senior Quantitative Risk Strategist is part of the Product organization and serves as a senior individual contributor responsible for designing, developing, validating, and optimizing quantitative risk models and analytical frameworks that protect Binance.US http://Binance.US customers, payment systems, and operations from fraud, financial crimes, account compromise, and payment-related losses. This role will act as the quantitative lead for payments risk, partnering closely with Product, Risk, Compliance, Engineering, Data, and Operations teams to develop scalable, data-driven risk solutions across customer onboarding, account funding, trading, and withdrawal experiences. The ideal candidate combines deep expertise in predictive modeling and risk analytics with practical experience managing fraud, ACH, card, and transaction risk within highly regulated financial services, fintech, or cryptocurrency environments. Success in this role requires balancing customer growth, conversion, and user experience with loss prevention, regulatory obligations, and operational efficiency. Core Responsibilities: Quantitative Risk Modeling & Analytics - Design, develop, deploy, and continuously improve predictive risk models, scoring methodologies, and decision frameworks across ACH deposits, wire transfers, debit card funding, withdrawals, account security, fraud, and cryptocurrency-related risk domains. - Build customer-level, transaction-level, and portfolio-level models that predict fraud losses, payment returns, chargebacks, account compromise, and emerging risk events. - Develop risk segmentation frameworks that dynamically assess customer behavior throughout the customer lifecycle, including onboarding, funding, trading activity, and withdrawals. - Apply advanced statistical methods, machine learning techniques, anomaly detection, and large-scale data analysis to identify evolving fraud patterns, abuse vectors, and operational vulnerabilities. Payments Risk Strategy - Quantify and monitor risk across payment rails, including ACH, wire, card, and other funding methods. - Develop forecasting methodologies for payment losses, ACH return rates, chargebacks, fraud exposure, and emerging risk trends. - Establish key risk indicators (KRIs), operational thresholds, portfolio health metrics, and executive reporting frameworks. - Evaluate the impact of new products, payment methods, customer segments, and growth initiatives through rigorous quantitative risk assessment. Risk Decisioning & Optimization - Partner with Product and Engineering teams to embed model-driven decisioning throughout the customer journey. - Design, test, and optimize risk rules, controls, decision engines, and transaction monitoring systems to maximize fraud prevention while minimizing customer friction. - Lead champion/challenger testing and experimentation frameworks to measure the effectiveness of risk controls and drive continuous improvement. - Quantify tradeoffs between fraud loss, customer conversion, operational efficiency, and business growth to support data-driven decision making. Investigations & Risk Governance - Conduct deep-dive investigations into material fraud events, payment losses, suspicious activity, and operational incidents, identifying root causes and recommending corrective actions. - Support model governance, validation, audit, and regulatory review activities through comprehensive documentation, monitoring, and control frameworks. - Establish model performance monitoring, calibration, and backtesting processes to ensure ongoing effectiveness and compliance. - Serve as a trusted advisor to senior leadership on payments risk, fraud analytics, financial crime risk, and cryptocurrency-related risk trends. Preferred Skills/Experience: - 8+ years of experience in quantitative risk analytics, fraud science, payments risk, machine learning, data science, or risk modeling within fintech, financial services, payments, banking, or cryptocurrency organizations. - Advanced degree in Statistics, Mathematics, Economics, Finance, Computer Science, Physics, Operations Research, Data Science, or a related quantitative discipline. Equivalent industry experience building and deploying production risk models will be strongly considered. - Advanced proficiency in SQL and strong experience with Python, Spark, R, or comparable analytical and modeling technologies. - Demonstrated success designing, deploying, validating, and monitoring predictive risk models in production environments. - Deep understanding of ACH payments, return codes, chargebacks, account takeover risk, first-party fraud, synthetic identity fraud, mule activity, payment abuse, and transaction risk management. - Experience developing portfolio-level forecasting models for fraud losses, payment returns, chargebacks, or credit-related risk outcomes. - Strong knowledge of AML regulations, sanctions compliance, KYC/KYB requirements, and financial crime risk management. - Experience supporting model governance programs, audit reviews, regulatory examinations, and independent model validation activities. - Familiarity with blockchain analytics platforms, cryptocurrency transaction monitoring solutions, and digital asset risk indicators. - Strong communication skills with the ability to translate complex quantitative findings into actionable business recommendations for both technical and executive audiences. Our Mission: At Binance.US http://Binance.US, our mission is to create a more inclusive financial system through Web3 technologies. As a U.S. regulated crypto platform, we’re committed to earning trust through compliance and empowering people to do more with their money, bringing financial freedom within reach for all. Our Values: Our values shape how we work, make decisions, and support our users every day: - Act with Integrity: We do what’s right, even when no one is watching. - Be Collaborative: We work together with respect and transparency to achieve shared goals. - Customers First: We listen to, advocate for, and prioritize our users in every decision we make. - Do the Work: We take ownership, follow through, and deliver results that move the mission forward. - Embrace Change: We stay adaptable and curious, thriving in a fast moving industry. Our Benefits: We believe in supporting our people with flexibility, balance, and opportunities to grow. One of the ways we demonstrate this commitment is through our benefit offerings. - Time & Family: Unlimited PTO (for salaried FTE roles); 12 weeks fully paid Parental Bonding Leave. - Well-Being: Mental wellness benefits; free 1:1 virtual visits with a licensed mental wellness professional; comprehensive competitive health benefits. - Remote-First Culture: Fully remote, cameras-on culture with work-from-home equipment reimbursements available to new hires. - Professional & Financial Growth: Annual professional development budget; free 1:1 virtual visits with a career coach; 401k plan with employer match. BAM Management US Holdings Inc. and BAM Management Canada Holdings Inc. are Equal Opportunity Employers and comply with all applicable federal, state, and local fair employment practice laws. Our mission is to give our customers access to a broad array of digital assets, and we thrive because of the diverse and inclusive team that we are building. We do not discriminate against qualified employees, applicants, or any other covered persons because of race, color, religion, creed, gender identity, sex, sexual preference, sexual identity, pregnancy, national origin, ancestry, citizenship, age, veteran status, physical disability, mental disability, medical condition, military status, or any other applicable legally protected characteristic. Depending on your location, data privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available here https://www.binance.us/privacy-policy#employee-applicants-privacy-notice. By submitting your application, you are agreeing to our use and processing of your data as required. We comply with Federal Transparency in Coverage regulations by providing a link to machine readable files related to the health plans offered to our employees. The machine-readable files are formatted to allow researchers, regulators, and application developers to more easily access and analyze data including negotiated service rates, and out-of-network allowed amounts between health plans and healthcare providers.", "summaryDescription" : "Senior Quantitative Risk Strategist at Binance. US. Skills: Quantitative risk modeling, Payments risk strategy, Risk decisioning, Fraud prevention. Design predictive risk models. 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Senior Product Quantitative Researcher, Cloud Security

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Measurement Analyst

Measurement Lead

Quantitative Researcher - Deep Learning

Associate/AVP, Quantitative Strategies Group

Principal Investigator, Quantum Error Correction

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Quantitative UX Researcher

Measurement Lead

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Senior Quantitative Risk Strategist

Internship – Quantitative Energy Systems Analysis

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