Cubist Systematic Strategies, LLC, has an opening for a Research Analyst in New York, New York. May work from home up to 1 day per week, as permitted.

Conduct and manage quantitative finance alpha research from diverse data sources to provide accurate stock return forecasts. Build and implement profitable quantitative equity investment models. Assist with generating trading strategies. Conduct research on and analyze large data sets. Gather investment thesis and author quantitative research reports and present research results to management and other team members. Collaborate with other members of the team (including developers and other researchers) in the full lifecycle R&D process from idea generation, data preparation, model building, implementation and production deployment. Play significant role in the design, building and maintenance of the team’s research and trading infrastructure and systems.

Must possess at least a master’s or its equivalent in Computational Finance, Financial Engineering, Statistics, Mathematics, Operations Research, Computer Science, or a related STEM field. Must also possess the following: at least one competitive internship in financial services; demonstrable experience with performing statistical analysis of historical data gathered from financial markets to build quantitative models; demonstrable experience with conducting independent research utilizing large data sets; demonstrable state of the art understanding of linear algebra and matrix mathematics; and demonstrable experience with programming/utilizing Python, C++ and SQL.

Approximately 40 hours per week; the salary range for this position is from $150,000 - $300,000 per year.

Any person who is interested in this position may apply to the following for consideration:

Send your resume to svcRecruiting@Point72.com and reference Job Code C052026K. 

Quantitative Trader (Job # ID: 00088964) (Tower Research Capital LLC; New York, NY):

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.

Minimum requirements: Bachelor’s degree or foreign equivalent in Mathematics, Statistics, Computer Science or a 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++.

Salary: $125,000.00 to $250,000.00 per year

Apply online at https://tower-research.com/open-positions/ or send resume to Tower HR at us-ta@tower-research.com & indicate job # ID 00088964. #LI-DNI

Point72, L.P. has an opening for a Quantitative Strategist, Treasury Quant Strategy in New York, New York. This position is hybrid; may work from home up to 2 days per week, as permitted.

Develop, implement, and maintain quantitative models for the Treasury function, including models for cash management, liquidity risk, and foreign exchange risk. Partner with Technology Teams to contribute to financing capabilities by delivering high quality calculations, contributing to Treasury’s analytic platform. Contribute quantitative solutions to shared repository and develop expertise across prime brokerage, financing models, and other firm models. Learn, model, and optimize margin across a variety of products. Develop tools to minimize securities financing fees across Treasury through convex optimization and enhancements to Treasury’s equity financing analytics platform. Build tools for exploring complex data sets and identifying day-over-day changes, whether market driven or due to changes in firm positioning. Own calculation of key treasury metrics, providing insights, advice, and quantitative leadership where required.

Must possess at least a master’s degree or its equivalent in Mathematics, Applied Mathematics, Statistics, or a related quantitative field and at least 5 years of work experience as a Quantitative Analyst/Strategist or in a related role. In the alternative, at least a PhD or its equivalent in Mathematics, Applied Mathematics, Statistics, or a related quantitative field and at least 2 years of work experience as a Quantitative Analyst/Strategist or in a related role would be acceptable. Must also possess the following: at least 2 years of experience with one of the varied Treasury domains, i.e. attribution models, margin calculations, cash management, capital utilization, and/or securities financing; at least 2 years of experience in a quantitative function within an equity financing role; at least 2 years of experience coding in Python; at least 2 years of experience contributing to a shared repository (git); and at least 2 years of experience in a production environment. Approximately 40 hours per week; the salary range for this position is from $228,000 to 300,000 per year.

Any person who is interested in this position may apply to the following for consideration:

Send your resume to svcRecruiting@Point72.com and reference Job Code M052026X.

Cubist Systematic Strategies, LLC, has an opening for a Research Analyst in New York, New York. This position is hybrid; may work from home up to 2 days per week, as permitted.

Conduct and manage quantitative finance alpha research from diverse data sources to provide accurate stock return forecasts. Build and implement profitable quantitative equity investment models. Assist with generating trading strategies. Conduct research on and analyze large data sets. Gather investment thesis and author quantitative research reports and present research results to management and other team members. Collaborate with other members of the team (including developers and other researchers) in the full life-cycle R&D process from idea generation, data preparation, model building, implementation and production deployment. Play significant role in the design, building and maintenance of the team’s research and trading infrastructure and systems.

Must possess at least a PhD or its equivalent in Statistics, Mathematics, Operations Research, Computer Science or a related STEM field and at least one year of experience as a Research Analyst, Data Scientist or a related role. Must also possess the following: at least one year of experience programming/utilizing SQL, C++ and Python; at least one year of experience conducting independent research utilizing large data sets; at least one year of experience building processes and technology to ingest, tag, and clean datasets; at least one year of experience building machine learning models; at least one year of experience using and analyzing high dimensional complex data; and at least one internship in finance working with financial and alternative data supporting a financial business and analyzing risk.

Approximately 40 hours per week; the salary range for this position is $160,000 to $300,000 per year

Any person who is interested in this position may apply to the following for consideration:

Send your resume to svcRecruiting@Point72.com and reference Job Code Z042026T.