Quantitative Research Intern (NLP)

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. They will develop strong research skills through working closely with our full-time researchers on brand new quant trading models with real-world impact. We will consider full-time offers for interns after the internship. Requirements: PhD candidate in math/physics/statistics/EE/CS, or other quantitative fields Strong knowledge of computational math, probability, and statistics Strong analytical skills, with attention to details Good communication skills Willing to work in a fast-paced start-u

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

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 ownership of his/her work, working well both independently and within a small collaborative team. We’re looking for exceptional colleagues with unparalleled passion. If you’d like your resume to stand out, tell us about your exceptional personal achievements, even if they have nothing to do with finance. Of course we love to hear more about specific engineering or data projects that you’ve worked outside of school, or as part of your curriculum. If you’re proud of the work you did we want to hear abou

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.

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