Quantitative Research Intern in New York

ROLE/RESPONSIBILTIES: We are seeking a quant research intern to join an NLP quant team within Point72. We believe the significant advances in NLP methods show promise for finance. We develop and launch end-to-end signals, from data processing to performance testing. The ideal candidate will have strong machine learning, data science and software engineering skills, some experience with modern NLP, and a curiosity about finance and trading. Responsibilities may include: Using NLP to construct features from varied datasets Formulating research hypotheses to derive alpha Building and testing the performance of trading signals based on NLP and financial features Launching identified signals into production REQUIREMENTS: Bachelor’s, Master’s or PhD candidate in computer science or other quantitative discipline Proficient in Python and general software engineering principles (github, testing, dev workflow) Strong understanding of machine learning and statistics Prior research experience preferred Experience with deep learning, specifically NLP (PyTorch, HuggingFace, LLMs, etc.) preferred Data science stack familiarity preferred An interest in financial markets Great attitude A collaborative mindset Commitment to the highest ethical standards ABOUT POINT72: Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systemati

Please send CVs to [email protected] with “202 7 QR Summer Internship Application” in the subject line. When your application is received, we will consider you for all similar positions at Cubist. About Our Firm: 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. Role / Experience: We are looking for exceptional students to be our quantitative researcher interns for the summer of 2027 . An ideal candidate should have a strong passion and initiative to work in a start-up environment. He/she should have strong analytical skills and be able to solve hard problems rigorously. Our typical intern candidates come from quantitative PhD programs of top US universities. Our internship program offers unique KEPL experience. During the internship, our interns will receive rigorous and comprehensive trainings

JOB RESPONSIBILITIES A highly collaborative, fast-growing team, Point72 Internal Alpha Capture (IAC) is developing scalable quantitative equity trading signals that leverage rigorous research, state-of-the-art machine learning methods, a broad range of public and proprietary data sources, and unparalleled computing power. We are looking for exceptional students to join us as quantitative researcher interns for Fall 2026, Spring 2027 and Summer 2027. Our interns will work closely with our team, receive comprehensive, in-depth training, and help develop novel signals that may have real impact. You will gain exposure to a variety of activities, which may include: Conducting full pipeline signal research, from ideation, via implementation and backtesting, to eventual application. Adapting and extending existing results in the broad field of machine learning; conducting novel research as needed to potentially develop new signals that may enhance portfolio returns. Analyzing very large data sets to extract features useful for predictive models. Providing research assistance to the team. Helping improve the team’s research infrastructure. DESIRABLE CANDIDATES Masters or PhD candidates in machine learning, computer science, finance, mathematics, or other quantitative disciplines. Demonstrated ability to conduct independent research utilizing machine learning over large, possibly noisy, data sets. Strong analytical and quantitative skills, and detail-oriented mindset. Proficient

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. RESPONSIBILITIES: Building components for both live trading and simulation Refining and increasing automation and robustness of the research infrastructure including alpha estimation, risk modeling, and backtesting components Building tools for signal blending, simulation, portfolio construction, the research framework, and dashboards Maintaining and updating the platform, ensuring its stability, robustness, and security Developing robust data checking and storage procedures Troubleshooting and resolving any systems related issues and handle the release of code fixes and enhancements REQUIREMENTS: Bachelor’s degree or higher in computer science or other STEM discipline Advanced proficiency in Python and its ecosystem (numpy, pandas, polars, scikit-learn), with an understanding of Python and library internals Experience contributing to core Python numerical libraries is a huge plus (numpy, tensorflow, torch, jax) Proficiency with Linux Hands-on experience with software architecture and engineering best practices (testing, CI/CD, monitoring, profiling, version control) Strong quantitative and analytical

JOB DESCRIPTION Researchers are responsible for applying, adapting, and extending existing results in the broad field of machine learning, while also conducting novel research as required. We are interested in all aspects of ML including: predictive modelling, clustering, time series analysis, natural language processing, and computer vision. Successful researchers manage all aspects of the research process including methodology selection, data collection and analysis, implementation and testing, prototyping, and performance evaluation. Some successful researchers have joined us from similar backgrounds at other firms. Others have joined from related fields or directly from academia and have thrived with hands on guidance from our large team of experienced portfolio managers and researchers. Our most exceptional team members combine strong technical skills and a passion for problem solving with an intense curiosity about financial markets and human behavior. DESIRABLE CANDIDATES Students enrolled in a PhD program in machine learning, computer science, statistics, or a related field. Superb analytical and quantitative skills, along with a healthy streak of creativity. Demonstrated ability to conduct independent research utilizing large data sets. Passion for seeing research through from initial conception to eventual application. Curiosity about financial markets Strong scientific programming in Python, R or Matlab. Empirical, detail-oriented mindset. Sense of owners

ROLE/RESPONSIBILTIES: We are seeking a NLP engineer for a NLP research team within Point72. The ideal candidate has a track record of developing modern NLP solutions, including the use of LLMs, agents, RAG, open-source models fine-tuning and deployment, etc. Responsibilities include: Exploring and combining rich internal and external textual datasets Building GenAI solutions, leveraging both internal models and external APIs Formulating research hypothesis to derive alpha Post-training models for specific tasks Benchmarking LLM approaches internal tasks We believe the investment world offers unique opportunities to use modern NLP methods. We are a team ideally situated for that, having access to both internal and commercial datasets, with an end-to-end research philosophy and direct portfolio impact. REQUIREMENTS: Bachelor, Master’s or PhD graduate or candidate in computer science or another quantitative discipline Experience in NLP, particularly LLMs. Proficient in Python, SQL and general software engineering principles (github, testing, etc.) Data science stack familiarity Interest in financial markets Collaborative mindset ABOUT POINT72: Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry’s b

ROLE We are passionate about data. We collaborate to build elegant, effective, scalable and highly reliable solutions to empower predictive modelling in finance. Cubist’s Data Services (CDS) group is looking for a Data Scientist to join our dedicated data team. Our group is responsible for the timely delivery of comprehensive and error-free data to some of the most demanding and successful systematic Portfolio Managers in the world. As a Senior Data Scientist in the team, this individual will play a vital role in ensuring the smooth day-to-day implementation of a large research infrastructure, and the live production trading of billions of dollars of capital across global capital markets, including equities, futures, options and other financial instruments. RESPONSIBILITIES Onboarding novel datasets from a huge variety of sources into our platform Building processes, tools and frameworks to ingest, clean and deliver datasets Analysis of data for usability, cleanliness, feature extraction and proposed usage by investment teams Creation of in-house, value added, derived data products for consumption by investment teams Engaging with vendors and internal stakeholders to understand characteristics of datasets Partnering closely with investment teams to ensure their data requirements are met Research on new technologies (including AI solutions) to continuously improve data management and value-add for investment teams REQUIREMENTS PhD or

ROLE We are passionate about data. We collaborate to build elegant, effective, scalable and highly reliable solutions to empower predictive modelling in finance. Cubist’s Data Services (CDS) group is looking for a Data Scientist to join our dedicated data team. Our group is responsible for the timely delivery of comprehensive and error-free data to some of the most demanding and successful systematic Portfolio Managers in the world. As a Data Scientist in the team, this individual will play a vital role in ensuring the smooth day-to-day implementation of a large research infrastructure, and the live production trading of billions of dollars of capital across global capital markets, including equities, futures, options and other financial instruments. RESPONSIBILITIES Onboarding novel datasets from a huge variety of sources into our platform Develop, test and deploy data pipelines, applications and services Re-shaping, aggregating, enhancing and creating features from datasets Engaging with vendors and internal stakeholders to understand characteristics of datasets Defining and automating qualitative data alerts and reports Partnering closely with investment teams to ensure their data requirements are met Perform preliminary analysis and research to be shared with investment teams REQUIREMENTS Masters in Financial Engineering, Statistics, Computer Science or other disciplines involving rigorous quantitative analysis Strong programming

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

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. JOB DESCRIPTION Researchers are responsible for independently conducting quantitative finance research with a focus on statistical and predictive models. Successful researchers manage all aspects of the research process including methodology selection, data collection and analysis, testing, prototyping, backtesting, and performance monitoring. Some successful researchers have joined us from similar backgrounds at other firms. Others have joined from related fields or directly from academia and have thrived with hands on guidance from our large team of experienced portfolio managers and researchers. Our most exceptional team members combine strong technical skills and a passion for problem solving with an intense curiosity about financial markets and human behavior. DESIRABLE CANDIDATES MS or PhD candidates in finance, computer science, mathematics, physics, or other quantitative discipline 3-7 years of experience in alpha driven quantitative research for equities, futures, fixed income, credit, and/or FX Strong analytical and quantitative skills Demonstrated ability to conduct independent research utili

Role/Responsibilities: We are seeking a quantitative researcher to join an NLP quant team within Point72. We believe the significant advances in NLP methods show promise for finance. We develop and launch end-to-end signals, from data processing to performance testing. The ideal candidate will have strong machine learning, data science and software engineering skills, some experience with modern NLP, and a curiosity about finance and trading. Responsibilities may include: Using NLP to construct features from varied datasets Formulating research hypotheses to derive alpha Building and testing the performance of trading signals based on NLP and financial features Launching identified signals into production Requirements: Bachelor’s, Master’s or PhD degree in computer science or other quantitative discipline Proficient in Python and general software engineering principles (github, testing, dev workflow) Strong understanding of machine learning and statistics Prior research experience preferred Experience with deep learning, specifically NLP (PyTorch, HuggingFace, LLMs, etc.) preferred Data science stack familiarity preferred An interest in financial markets Great attitude A collaborative mindset Commitment to the highest ethical standards About Point72: Point72 Asset Management is a global firm led by Steven Cohen that invests in multiple asset classes and strategies worldwide. Resting on more than a quarter-century of investing experience, we seek to be the industry’s premier a

Role/Responsibilities Research and develop in-house trading strategies, used by both discretionary and quantitative traders. Conduct quantitative research on market microstructure, applying knowledge to improve trading algorithm and identify market anomalies. Develop and maintain predictive models to optimize trade execution and minimize transaction costs, utilizing both linear and non-linear techniques. Collaborate with cross-functional teams, including portfolio managers and researchers, to design and implement solutions for the trading strategies. Stay current and report on changes in market microstructure. Requirements Master's degree or higher in a quantitative field such as Finance, Mathematics, Statistics, Computer Science, or a related discipline. A minimum of 2 years of experience in quantitative research, building statistical models for intraday study. Solid understanding of market impact. Proficiency in programming languages such as Python and C++. Experience in AWS is preferred. Strong knowledge in macro products, including FX and bonds, is a plus. Commitment to the highest ethical standards. The annual base salary range is $125,000-200,000 (USD). Actual compensation offered to candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level among other things. Details about eligibility for bonus compensation (if applicable) will be finalized at the time of offer.

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 alg

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 researc

About the Team: A well-established quantitative portfolio management team at Point72 is looking for an experienced quantitative professional to develop and trade systematic macro strategies, with a focus on market microstructure. The candidate will be given the resources and support to drive the build out and expansion of the quantitative macro business. Role/Responsibilities: Perform rigorous and innovative research to develop systematic signals for global macro (futures, FX, etc.) markets, with a focus on market microstructure signals Perform feature engineering with order book tick data at intraday to daily horizons Perform feature combination using various modeling techniques ranging from linear to machine learning models Participate in the research pipeline end-to-end, including signal idea generation, data processing, modeling, strategy backtesting, and production implementation Help drive the growth of the investment process and research capabilities of the team Work in a team of highly qualified and motivated individuals with access to a cutting-edge research and trading infrastructure and clean datasets Assist in building, maintenance, and continual improvement of production and trading environments Requirements: MS or PhD in physics, engineering, statistics, applied math, quantitative finance, or other quantitative fields with a strong foundation in statistics 4+ years of experience in quantitative research, building statistical models for intraday to daily trading,