Microstructure 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
- Develop systematic signals for global macro markets, concentrating on market microstructure
- Build features from order book tick data and combine them with methods ranging from linear models to machine learning
- Take research from signal ideas through data preparation, modeling, backtests and production rollout
- Help expand the team's investment process and research capabilities
- Maintain and improve production and trading environments
What you bring
- An MS or PhD in a quantitative field, with a strong grounding in statistics
- At least four years building statistical models for intraday-to-daily trading research on a successful proprietary trading team
- Knowledge of futures or FX market microstructure, plus experience generating, modeling and monetizing features from tick data
- Proficiency in Python, R or C/C++, with familiarity with data science libraries such as scikit-learn or Pandas
Who this fits
This mid-level role suits a quantitative researcher who can work independently on research while collaborating with a team. The position is based in New York.
From the employer
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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