Quantitative Research Intern Jobs

At Trustpilot, we're on an incredible journey. We're a profitable, high-growth FTSE-250 company with a big vision: to become the universal symbol of trust. We run the world's largest open customer review platform, and while we've come a long way, there's still so much exciting work to do. Come join us at the heart of trust! We’re a leading online reviews platform, free and open to all. Our mission is to be a universal symbol of trust. We are well on our way - but there’s still an exciting journey ahead of us. Do you want to join us at the heart of trust? We’re currently looking for a Senior UX researcher to join our team at Trustpilot. Our goal is simple: to become the most trusted reviews platform in the world. We will achieve this by being ready and willing to disrupt ourselves through innovation, data and insight and adding product professionals with ambitions that match our own. As Senior UX Researcher, you'll be the go-to expert on measuring how people and businesses experience trust on Trustpilot , from reading a review to deciding our platform is worth paying for. You'll own the quantitative research agenda for your product areas, set the bar for statistical rigour across the team, and partner with Data Science to build a shared measurement culture. What you'll be doing: Research strategy & execution Design and own the quantitative research roadmap for your product areas, e.g. attitudinal measurement, behavioural analysis, and longitudinal tracking. Lead large-scale surveys (validated scales, NPS derivatives, trust-perception metrics) and log-data/behavioural analytics (funnels, A/B tests, cohort and retention modelling). Build measurement frameworks that define what ‘good’ looks like for review-reading, purchase-decision, and business-subscription journeys and track them over time. Quantitative methods Lead advanced quantitative research - surveys, behavioural analytics, experimentation, predictive modelling using statistical rig

At Trustpilot, we're on an incredible journey. We're a profitable, high-growth FTSE-250 company with a big vision: to become the universal symbol of trust. We run the world's largest open customer review platform, and while we've come a long way, there's still so much exciting work to do. Come join us at the heart of trust! We’re a leading online reviews platform, free and open to all. Our mission is to be a universal symbol of trust. We are well on our way - but there’s still an exciting journey ahead of us. Do you want to join us at the heart of trust? We’re currently looking for a Senior UX researcher to join our team at Trustpilot. Our goal is simple: to become the most trusted reviews platform in the world. We will achieve this by being ready and willing to disrupt ourselves through innovation, data and insight and adding product professionals with ambitions that match our own. As Senior UX Researcher, you'll be the go-to expert on measuring how people and businesses experience trust on Trustpilot , from reading a review to deciding our platform is worth paying for. You'll own the quantitative research agenda for your product areas, set the bar for statistical rigour across the team, and partner with Data Science to build a shared measurement culture. What you'll be doing: Research strategy & execution Design and own the quantitative research roadmap for your product areas, e.g. attitudinal measurement, behavioural analysis, and longitudinal tracking. Lead large-scale surveys (validated scales, NPS derivatives, trust-perception metrics) and log-data/behavioural analytics (funnels, A/B tests, cohort and retention modelling). Build measurement frameworks that define what ‘good’ looks like for review-reading, purchase-decision, and business-subscription journeys and track them over time. Quantitative methods Lead advanced quantitative research - surveys, behavioural analytics, experimentation, predictive modelling using statistical rig

At Trustpilot, we're on an incredible journey. We're a profitable, high-growth FTSE-250 company with a big vision: to become the universal symbol of trust. We run the world's largest open customer review platform, and while we've come a long way, there's still so much exciting work to do. Come join us at the heart of trust! We’re a leading online reviews platform, free and open to all. Our mission is to be a universal symbol of trust. We are well on our way - but there’s still an exciting journey ahead of us. Do you want to join us at the heart of trust? We’re currently looking for a Senior UX researcher to join our team at Trustpilot. Our goal is simple: to become the most trusted reviews platform in the world. We will achieve this by being ready and willing to disrupt ourselves through innovation, data and insight and adding product professionals with ambitions that match our own. As Senior UX Researcher, you'll be the go-to expert on measuring how people and businesses experience trust on Trustpilot , from reading a review to deciding our platform is worth paying for. You'll own the quantitative research agenda for your product areas, set the bar for statistical rigour across the team, and partner with Data Science to build a shared measurement culture. What you'll be doing: Research strategy & execution Design and own the quantitative research roadmap for your product areas, e.g. attitudinal measurement, behavioural analysis, and longitudinal tracking. Lead large-scale surveys (validated scales, NPS derivatives, trust-perception metrics) and log-data/behavioural analytics (funnels, A/B tests, cohort and retention modelling). Build measurement frameworks that define what ‘good’ looks like for review-reading, purchase-decision, and business-subscription journeys and track them over time. Quantitative methods Lead advanced quantitative research - surveys, behavioural analytics, experimentation, predictive modelling using statistical rig

We’re building a new quantitative research team focused on pricing, market-making, and risk models for prediction markets. This is a highly hands-on role for someone who can operate end-to-end: data engineering, research, modeling, and close collaboration with traders, across sports and non-sports event markets and a range of contract types, including single-outcome markets, player props, and parlays. Responsibilities: Build data foundation, transform raw data into pricing inputs Research and develop quantitative pricing, market-making, and risk models across sports, non-sports, player props, parlays, and correlated markets Model cross-market dependencies, correlations, and portfolio effects, especially for combinatorial products such as parlays Partner closely with traders to improve pricing logic, market coverage, and trading performance Build frameworks for backtesting, simulation, and model validation Create tools to monitor model performance, calibration, P&L attribution, and live trading outcomes Help define the tooling, workflow, and research standards for a new team Requirements: Strong quantitative background in statistics, math, ML, economics, or a related field Experience building models in trading, sports, betting, prediction markets, or similar domains Strong Python/data skills and comfort owning data pipelines as well as modeling Ability to move quickly from raw data to research insight to production-ready mode High ownership, strong communication skills and comfortable with fast-paced high growth environment Life @ Crypto.com Empowered to think big. Try new opportunities while working with a talented, ambitious and supportive team. Transformational and proactive working environment. Empower employees to find thoughtful and innovative solutions. Growth from within. We help to develop new skill-sets that would

Role Quantitative Researcher for a new team focused on systematic corporate bond and credit derivatives strategies. Responsibilities Independently conduct quantitative research, adopting a rigorous approach and using statistical and structural models Contribute to all aspects of the research and production process, including implementation of fitting tools; data organization; generation of alphas, risk and TC models; P&L attribution, etc. Proactively search for and prioritize new ideas and datasets for alpha potential Contribute to continuous improvement of the investment process and infrastructure in collaboration with the portfolio managers, developers and traders on the team Requirements PhD or Master’s degree in Economics, Finance, Statistics, Mathematics, Physics, or other quantitative discipline 2+ years of experience developing statistical and fundamental alpha signals, risk factors for single name credit, equities, or options. Demonstrated ability to conduct research utilizing large data sets Experience with FICC, credit or option pricing models is preferred Experience with numerical optimization methods is a plus Solid programming skills: understanding of the object-oriented programming and CI/CD framework. Proficiency in Python, including with packages used for data research, best practices of coding style, etc. ­ Strong communication skills Willingness to take ownership of his/her work, working both independently and within a team The annual base salary range for this role is $150,000-$200,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.

Become a part of our caring community The Research Scientist 2 participates in research study design, analysis and interpretation of results, with special emphasis on statistical and analytical plan development; data acquisition, preparation, and management; statistical analysis and interpretation of findings. The Research Scientist 2 work assignments are varied and frequently require interpretation and independent determination of the appropriate courses of action. Humana’s Healthcare Quality & Reporting Improvement (HQRI) department is seeking a Research Scientist 2 to join a high-performing team dedicated to advancing predictive modeling and analytics in support of our Medicare and Medicaid business. The HQRI team plays a pivotal role within Humana, delivering insights that drive the effectiveness of risk adjustment initiatives. In this position, the Research Scientist 2 will partner with a senior research scientist to apply advanced statistical methods to rigorously evaluate the impact of risk adjustment programs and pilot projects. The findings generated will be critical in informing key business decisions and optimizing operational strategies. Additionally, the person in this role will collaborate with colleagues specializing in data science and actuarial analytics. We are seeking a candidate who brings complementary skills to the team, with the ability to learn from their teammates while contributing with their unique expertise in statistical analysis. Use your skills to make an impact Required Qualifications Bachelor's degree in Computer Science, Data Science, Mathematics or a related quantitative field; 2 years of experience applying statistical modeling, pred

ABOUT CUBIST Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. WHAT YOU'LL DO The Quant Developer will be responsible for building and maintaining the research infrastructure and backtesting frameworks that support quantitative research, working closely with researchers to translate research ideas into robust, scalable, and maintainable research systems. The role spans multiple areas, including system design, data pipeline development, and the development of research and backtesting frameworks. WHAT'S REQUIRED Background in Electrical Engineering, Computer Science, or a related field, with 3+ years of software development experience as a software engineer. Strong programming ability in C++ and Python. Solid command of CI/CD practices and tooling, with the ability to design and maintain automated testing and build pipelines for research and backtesting environments. Practical knowledge and hands-on experience with distributed computing and distributed job scheduling / task assignment. Excellent analytical and engineering problem-solving skills. Demonstrated ability to work independently on large datasets and large codebases. A strong team player who works closely with researchers to translate research ideas into stable, maintainable research systems. Willingness to take ownership of your work, able to operate both independently and within a small team, while remaining careful, detail-oriented, and capable of performing well under pressure. Strong English communication skills. Commitment to the highest ethical standards. We take care of our people We invest in our people, their careers, their health, and their well-being. When you work here, we provid

Point72 is seeking a Quantitative Developer to join its Portfolio Construction and Analysis (PCA) team within the CIO office. ROLE Point72 is seeking a Quantitative Developer to join its Portfolio Construction and Analysis (PCA) team within the CIO office. The PCA team plays a vital role in the Equity L/S business at the firm, collaborating with investment teams to improve net revenue and risk adjusted returns. The Quantitative Developer will build, refine, and maintain an efficient technology infrastructure to enable and support the team’s quantitative research and analytical efforts. The ideal candidate is a smart, self-driven, and creative problem solver with strong technical and quantitative skills. RESPONSIBILITIES Architect, build, refine, and increase automation and robustness of the research infrastructure, including data access, risk modeling, and backtesting components Collaborate with quant researchers to implement framework for automating and presenting analytics, reports, and monitors Collaborate with firm-wide technology teams to deliver analytics and tools to users across the firm DESIREABLE CANDIDATES Undergraduate, Masters, or PhD in Computer Science or other quantitative discipline 3+ years of professional experience developing infrastructure to support an investment team Strong programming skills in Python and SQL Solid background in math/statistics/finance and familiarity with quantitative research methodologies and machine learning algorithms Understanding of and experience with the data ingestion process Ability to contribute to the analytics, quant research, and development process Understanding of portfolio construction is a plus Knowledge of equities is a plus High-energy personality and the ability to manage multiple tasks and deadlines in a fast-paced environment High degree of drive – must be a self-starter Ability to recognize and seize opportunities Depth of skills enabling him/her to perform ad hoc projects and task

Please send CVs to [email protected] with “202 7 KEPL Application” in the subject line. About Cubist: Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. About Our Team: KEPL is a fast-growing team at Cubist Systematic Strategies. We specialize in trading medium-frequency statistical arbitrage strategies with high Sharpe. The team is made up of people from top universities and top tier trading and tech firms. We have an open and collaborative culture, and we value rigorous research and innovative technologies. We are actively expanding into new markets and assets classes. Role: We are looking for full-time quantitative research analysts and software developers to join our fast-growing team and contribute to multiple new initiatives that aim to expand our business. The candidate should have a passion for innovation to solve research and trading problems. In this team, the candidate will gain full-stack exposure and build expertise in multiple aspects of quantitative research and trading. The candidate will play an essential role for the team’s successful expansion. The candidate will also collaborate with other team members to innovate our research infrastructure which will take our research and trading capability to the next level. Responsibilities: Conduct quantitative research to support the team’s investment process. Build technologies that bolster research & trading productivity. Develop, maintain, and improve the production trading capacity. Expand the system to new markets and asset classes. Requirements: Master or PhD degree in math, physics, computer science, engineering, or other related discipline. 1-3 years of prof

JOB DESCRIPTION Point72 Asset Management is seeking a Quantitative Analyst to join its Portfolio Construction & Analytics Team (PCAT) in the Office of the CIO. PCAT’s mandate is to study all drivers of success for Long/Short Equities investment professionals using data, analytics, and models of investor behavior and the market. These analyses are shared with portfolio managers to improve their strategies and with senior management to better allocate capital across investment teams. The ideal candidate is a highly analytical and creative problem-solver who can conduct independent research, work effectively as part of a team, and effectively summarize and communicate findings. RESPONSIBILITES Conduct bottoms-up analysis on the firm’s portfolios to identify strengths and weaknesses in idea generation, trading, and construction Form top-down views on which strategies offer the best risk/reward for the firm Invent new analytics to quantify skill and frameworks to support trade-offs between different sources of skill and risk Quantify market drivers to support pre-trade risk taking and decision making Communicate key findings to the team, PMs, and Co-CIOs Learn to develop in and contribute back to shared code base, reports, and research tools DESIRABLE CANDIDATES 2 or more years of experience in a quantitative research, portfolio management, or risk management role dealing with equities or equities investments Undergraduate, MS or Ph.D. in Finance, Computer Science, Mathematics, Engineering, or Physics, or other quantitative discipline Experience with statistical models and essential methods of quantitative finance Some level of proficiency in quantitative programming (Python preferred) Highly analytical Good interpersonal skills Detail-oriented Self-starter Ability to work cooperatively in a team-oriented, fast-paced environment A commitment to the highest ethical standards and to act with professionalism and integrity Point72 is a leading global

About BlockTech BlockTech is a fast-paced algorithmic trading firm trading crypto derivatives and spot across global venues, 24/7, with our own capital. Crypto is one of the few markets where a researcher can still move the edge. The data is abundant, the microstructure is novel, and the loop between an idea and live PnL is short. High-frequency options trading is where we're strongest, and we're widening our scope to include more mid-frequency work. We're looking for a senior Quantitative Researcher with a mid-frequency background to join our Amsterdam trading floor. The role You'll be in charge of developing our mid-frequency capabilities, owning the research agenda end to end, from hypothesis and dataset construction through model training and backtesting to live deployment. You'll sit with traders, researchers, and analysts, and raise the bar for research across the floor. You will: Own price-prediction, signal, execution, and anomaly-detection models across crypto derivatives and spot markets from idea to live PnL Shape our research, backtesting, and trading infrastructure together with engineers, so good ideas reach production quickly and safely Own models in production: monitor live performance, diagnose decay, and iterate on what you ship Set research direction alongside traders, deciding which trades are worth making and why Raise the research bar by mentoring colleagues, reviewing work, and setting standards for rigour What we're looking for 3+ years of quantitative research experience at a hedge fund, trading firm, or similar, with mid-frequency models you've taken live A strong academic foundation in a quantitative discipline (mathematics, physics, statistics, or computer science) Fluency in Python and the modern ML stack (PyTorch and/or TensorFlow, scikit-learn, NumPy, pandas) A deep grasp of overfitting, validation design, and feature engineering. You can explain why a model works, not just that it does Software engineering instincts: you write product

About BlockTech BlockTech is an algorithmic trading firm operating at the frontier of global crypto derivatives and spot markets. We trade 24/7 across some of the fastest-moving, most data-rich venues in finance. Crypto remains one of the few markets where a researcher can still meaningfully move the edge: abundant data, novel microstructure, and the shortest possible loop between a research idea and live PnL. We're looking for an experienced Quantitative Researcher to take ownership of that edge and push it further. The role This is a senior, hands-on research seat on our trading floor. You'll own a research agenda end-to-end from hypothesis, dataset construction, feature engineering, model training, backtesting, live deployment, monitoring, and iteration. You'll be trusted to set its direction. You'll work shoulder-to-shoulder with fellow researchers, traders and analysts, shape how we price and trade, and help raise the bar for research across the floor, including mentoring less experienced researchers and influencing the tools and standards the team relies on. You will: Own price-prediction, signal, execution, and anomaly-detection models across crypto derivatives and spot markets from idea to live PnL using state-of-the-art ML Shape our research, backtesting, and trading infrastructure together with engineers, so good ideas reach production quickly and safely Own models in production: monitor live performance, diagnose decay, and iterate on what you ship Set research direction alongside traders, deciding which trades are worth making and why Raise the research bar by mentoring colleagues, reviewing work, and setting standards for rigour What we're looking for 4+ years of hands-on quantitative research and/or applied ML experience, with a track record of models you've taken into production trading live A strong academic foundation in a quantitative discipline (mathematics, physics, statistics, computer science, ML/AI, or similar) Fluency in Python and the modern

About BlockTech BlockTech is an algorithmic trading firm operating at the frontier of global crypto derivatives and spot markets. We trade 24/7 across some of the fastest-moving, most data-rich venues in finance. Crypto remains one of the few markets where a researcher can still meaningfully move the edge: abundant data, novel microstructure, and the shortest possible loop between a research idea and live PnL. We're looking for an experienced Quantitative Researcher to take ownership of that edge and push it further. The role This is a senior, hands-on research seat on our trading floor. You'll own a research agenda end-to-end from hypothesis, dataset construction, feature engineering, model training, backtesting, live deployment, monitoring, and iteration. You'll be trusted to set its direction. You'll work shoulder-to-shoulder with fellow researchers, traders and analysts, shape how we price and trade, and help raise the bar for research across the floor, including mentoring less experienced researchers and influencing the tools and standards the team relies on. What you'll do Own price-prediction, signal, execution, and anomaly-detection models across crypto derivatives and spot markets from idea to live PnL using state-of-the-art ML Shape our research, backtesting, and trading infrastructure together with engineers, so good ideas reach production quickly and safely Own models in production: monitor live performance, diagnose decay, and iterate on what you ship Set research direction alongside traders, deciding which trades are worth making and why Raise the research bar by mentoring colleagues, reviewing work, and setting standards for rigour What we're looking for 4+ years of hands-on quantitative research and/or applied ML experience, with a track record of models you've taken into production trading live A strong academic foundation in a quantitative discipline (mathematics, physics, statistics, computer science, ML/AI, or similar) Fluency in Python and the m

About BlockTech BlockTech is an algorithmic trading firm operating at the frontier of global crypto derivatives and spot markets. We trade 24/7 across some of the fastest-moving, most data-rich venues in finance. Crypto remains one of the few markets where a researcher can still meaningfully move the edge: abundant data, novel microstructure, and the shortest possible loop between a research idea and live PnL. We're looking for an experienced Quantitative Researcher to take ownership of that edge and push it further. The role This is a senior, hands-on research seat on our trading floor. You'll own a research agenda end-to-end from hypothesis, dataset construction, feature engineering, model training, backtesting, live deployment, monitoring, and iteration. You'll be trusted to set its direction. You'll work shoulder-to-shoulder with fellow researchers, traders and analysts, shape how we price and trade, and help raise the bar for research across the floor, including mentoring less experienced researchers and influencing the tools and standards the team relies on. You will: Own price-prediction, signal, execution, and anomaly-detection models across crypto derivatives and spot markets from idea to live PnL Shape our research, backtesting, and trading infrastructure together with engineers, so good ideas reach production quickly and safely Own models in production: monitor live performance, diagnose decay, and iterate on what you ship Set research direction alongside traders, deciding which trades are worth making and why Raise the research bar by mentoring colleagues, reviewing work, and setting standards for rigour What we're looking for 4+ years of hands-on quantitative research and/or applied ML experience, with a track record of models you've taken into production trading live A strong academic foundation in a quantitative discipline (mathematics, physics, statistics, computer science, ML/AI, or similar) Fluency in Python and the modern ML stack (PyTorch and/or

About BlockTech BlockTech is an algorithmic trading firm operating at the frontier of global crypto derivatives and spot markets. We trade 24/7 across some of the fastest-moving, most data-rich venues in finance. Crypto remains one of the few markets where a researcher can still meaningfully move the edge: abundant data, novel microstructure, and the shortest possible loop between a research idea and live PnL. We're looking for an experienced Quantitative Researcher to take ownership of that edge and push it further. The role This is a senior, hands-on research seat on our trading floor. You'll own a research agenda end-to-end from hypothesis, dataset construction, feature engineering, model training, backtesting, live deployment, monitoring, and iteration. You'll be trusted to set its direction. You'll work shoulder-to-shoulder with fellow researchers, traders and analysts, shape how we price and trade, and help raise the bar for research across the floor, including mentoring less experienced researchers and influencing the tools and standards the team relies on. What you'll do Own price-prediction, signal, execution, and anomaly-detection models across crypto derivatives and spot markets from idea to live PnL using state-of-the-art ML Shape our research, backtesting, and trading infrastructure together with engineers, so good ideas reach production quickly and safely Own models in production: monitor live performance, diagnose decay, and iterate on what you ship Set research direction alongside traders, deciding which trades are worth making and why Raise the research bar by mentoring colleagues, reviewing work, and setting standards for rigour What we're looking for 4+ years of hands-on quantitative research and/or applied ML experience, with a track record of models you've taken into production trading live A strong academic foundation in a quantitative discipline (mathematics, physics, statistics, computer science, ML/AI, or similar) Fluency in Python and the m