Microstructure Quantitative Researcher
- LocationNew York
- Work typeOn-site
- Posted22 October 2026
- SourcePoint72's careers page (Greenhouse)
Live checkFirst seen 11 days ago; still listed on Point72's careers page 1 h ago.
Moves fastWhen Point72 takes a role down early, it is usually about 8 days after posting. Apply soon.
At a glance
- Experience4+ years
- EducationMaster's degree
- Skills and toolsMachine learning, Python, scikit-learn
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About the role
About the Team:
A well-established quantitative portfolio management team at Point72 is looking for an experienced quantitative professional to develop and trade systematic macro strategies, with a focus on market microstructure. The candidate will be given the resources and support to drive the build out and expansion of the quantitative macro business.
Role/Responsibilities:
- Perform rigorous and innovative research to develop systematic signals for global macro (futures, FX, etc.) markets, with a focus on market microstructure signals
- Perform feature engineering with order book tick data at intraday to daily horizons
- Perform feature combination using various modeling techniques ranging from linear to machine learning models
- Participate in the research pipeline end-to-end, including signal idea generation, data processing, modeling, strategy backtesting, and production implementation
- Help drive the growth of the investment process and research capabilities of the team
- Work in a team of highly qualified and motivated individuals with access to a cutting-edge research and trading infrastructure and clean datasets
- 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 experience in quantitative research, building statistical models for intraday to daily trading, as part of a successful proprietary trading team with a track record
- Knowledge of market microstructure for futures and/or FX
- Prior experience with tick data based feature generation, modelling, and monetization
- 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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