Quantitative Analyst / Software Developer

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

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 in Python or C++, and Linux environment. Excellent written and verbal communication skills, willing to proactively engage other team members in helping to foster a highly collaborative, team-oriented research environment. Willing to take ownership of his/her work, working both independently and within a collaborative team. Prior experience in the financial services industry is not required. Commitment to the highest ethical standards. The annual base salary range is $120000.00-$180000.00&n

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.

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. Role Quantitative researcher to help build out a systematic macro (futures, FX, and vol) strategies. Core focus will be working on mid-frequency alpha strategies. Job Description Develop systematic trading models across FX, commodities, fixed income, and equity markets Alpha idea generation, backtesting, and implementation Assist in building, maintenance, and continual improvement of production and trading environments Evaluate new datasets for alpha potential Improve existing strategies and portfolio optimization Execution monitoring Be a core contributor to growing the investment process and research infrastructure of the team Desirable Candidates Masters or PhD in mathematics, statistics, physics or other quantitative discipline. PhD in statistics or machine learning is a plus Experience in quantitative trading, ideally in FX or futures Experience with alpha research, portfolio construction and optimization Experience building statistical/technical, fundamental, and data driven signals Experience synthesizing predictive signals for both cross-sectional and time-series models Strong experience with data exploration, dimension reduction, and feature engineering Thorough understanding of and comfort using a variety of regression techniques—including OLS, MLS, Ridge, Lasso, and Bayesian inference—as well as techniques for dealing with errors that can occur, such as auto-correlation and heteroskedasticity Experience managing and running risk is a strong plus Proficiency in Python using the machine learning stack—numpy, pandas, scikit-learn, etc. Creative mindset Strong time management abi

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 systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry’s brightest talent by cultivating an investor-led culture and committing to our people’s long-term growth.

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 are specialized in 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, including: D.E. Shaw, Two Sigma, Citadel, Meta, Google, etc. We have an open and collaborative culture, and we value rigorous research and innovative technologies. Please send CVs to [email protected] with “2026 KEPL QD Application” in the subject line. Role: We are looking for a quantitative software developer to join our team and contribute to multiple initiatives that aim to expand our business. The candidate should be passionate about financial market, data and technology. In this team, the candidate will gain full-stack exposure and build expertise in multiple aspects of quantitative trading. Responsibilities: Improve data ETL pipeline and build tools to analyze new data efficiently. Build technologies to bolster research & trading efficiency. Expand to new markets and asset classes. Manage day-to-day operations in a fast-paced environment. Requirements Master/PhD degree in math, computer science, engineering, or other related fields. 1-3 years of professional experience in software development or data science/analytics. Strong combination of quantitative skills and programming skills. Proficiency in Python; knowledge of common data analytics tools (e.g., SQL, pandas) is a plus. Familiarity with the Linux environment. Excellent written and verbal communication skills. Willing to work in a fast-paced start-