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Fund Flow Quantitative Researcher

Point72 · Venture Capital · Hedge Funds & Alternative Investments · Master's Degree · Python · 1 month ago

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Salary

≈ $167k – $364k per year (Estimated)

Location

In office (New York)

Visa

H-1B filings in 12 months: 83 · for this role: 21 · green card filings: 20

Confirmed on the employer's own hiring board on Oct 28, 2026. First seen by Alion on Jan 23, 2026. Point72 scores B on the Alion truth index.

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Point72

Point72 is an American investment firm founded in 2014 when Steven Cohen converted his former hedge fund SAC Capital into a family office, before reopening to outside capital in 2018. It runs a multi-strategy business dominated by discretionary long and short equity teams organised as independent portfolio managers, alongside macro, systematic and quantitative strategies that rely heavily on alternative data and machine learning. Headquartered in Stamford, Connecticut with offices across North America, Europe and Asia, it also operates Point72 Ventures as a venture capital arm and runs a well-known academy programme that trains analysts from outside finance.

point72.com · HQ: Stamford, United States · Venture Capital · Hedge Funds & Alternative Investments · 1001-5000 employees · Est. 2014

Backed by Point72 Ventures - Venture Capital Firm

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

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