Fund Flow Quantitative Researcher

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Data From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Company

Equity

Offered From the posting source checked Jun 20, 2026

Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Fund Flow Quantitative Researcher New York, Stamford, London Role: Point72 is looking for a Quantitative Researcher to join its Fund Flow Research team. The Fund Flow Group provides best in class flow and positioning indicators to help PMs, analysts, and traders across all investment functions understand their investment backdrop, better assess reward and risk, and identify alpha opportunities. Responsibilities : - Create systematic trading strategies for macro and equity markets using proprietary flow and positioning datasets - Conduct rigorous applied research to develop systematic signals for macro and equity markets, with a focus on investor flows and positioning - Contribute to all aspects of the research and production process, including idea generation, hypothesis testing, portfolio construction, risk and transaction cost models, and P&L attribution - Monitor, analyze and improve live trading P&L - Collaborate with analysts and strategists to improve PM-facing content Requirements: - Undergraduate, Master's or PhD candidates in a technical field - Demonstrated creativity and rigor in the research process - Technically comfortable handling large datasets stored in AWS using Python - Collaborative mindset - Passion for research and financial markets - Intellectual curiosity, exceptional attention to detail, and the ability to manage multiple projects and deadlines in a fast-paced environment - Commitment to the highest ethical standards

Read the full description at boards.greenhouse.io. FewerJobs shows a preview and links to the original posting.