This posting is no longer listed by Point72.
hirly last saw it live on 1 September 2026. Similar roles are on the live board.
Point72
Macro Quantitative Researcher
New York
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hirly's read of this role
- Seniority
- Mid level
- Country
- US
- Work mode
- On-site / unstated
- First seen by hirly
- 1 Sept 2026
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the posting
About the Team:
A well-established quantitative portfolio management team at Point72 is looking for an experienced quantitative professional in the intraday to mid frequency systematic macro space. The candidate will be given the resources and support to drive the build out and expansion of the quantitative macro business.
Role:
Perform rigorous and innovative research to develop systematic signals for global macro (futures, FX, etc.) markets
Work with price-volume and alternative data at intraday to multiday (up to 2-3 weeks) horizons in the mid-frequency space
Participate in the research pipeline end-to-end, including signal idea generation, data processing, modeling, strategy backtesting, and production implementation
Work in a team of highly qualified and motivated individuals with access to a cutting-edge research and trading infrastructure and clean datasets
Responsibilities:
Develop systematic trading models across global futures (equity indices, commodities and fixed income) and/or FX markets
Alpha idea generation, backtesting, and implementation
Evaluate new datasets for alpha potential
Contribute to and enhance portfolio optimization, allocation and risk management processes
Help drive the growth of the investment process and research capabilities of the team
Assist in building, maintenance, and continual improvement of production and trading environments
Requirements:
MS or PhD in physics, engineering, statistics, applied math, quantitative finance, or other quantitative fields with a strong foundation in statistics
4+ years of signal research or portfolio management experience in futures markets and/or FX as part of a successful proprietary trading team with a track record
Prior professional experience with signal combination, portfolio optimization and risk management
Demonstrated proficiency in Python, R, or C/C++. Familiarly with data science toolkits, such as scikit-learn, Pandas
Collaborative mindset with strong independent research abilities
Commitment to the highest ethical standards
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