Fund Flow Quantitative Researcher
At a glance
Mid-level Data Science role at Point72. New York · full-time · no salary stated · we estimate $137,581–$208,900.
Point72 has not published a salary for this role. The figure below is our estimate, not theirs.
dataroles summary, based on the employer's posting.
What you'll do
- Build systematic strategies for macro and equity markets from the team’s flow and positioning data
- Research signals based on investor activity and positioning across macro and equity markets
- Take research from idea development through testing, portfolio design, risk and trading-cost models, and P&L analysis
- Track live strategy results, investigate performance, and make improvements
- Work with analysts and strategists to strengthen material for portfolio managers
What you bring
- You are pursuing an undergraduate, master’s, or doctoral degree in a technical discipline
- You can use Python to work with large datasets held in AWS
- You bring creativity and rigor to research, along with a strong interest in research and financial markets
- You show careful attention to detail and can juggle projects and deadlines in a fast-moving setting
Who this fits
This role suits a technically trained researcher who is curious about financial markets and works well with others. The position is based in New York and is listed as full-time.
From the employer
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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