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Point72

Microstructure Quantitative Researcher

Posted 17 Days Ago
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In-Office
New York, NY
Senior level
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In-Office
New York, NY
Senior level
The role involves conducting research to develop systematic macro strategies and signals focusing on market microstructure for trading. Responsibilities include feature engineering, modeling, backtesting, and improving trading environments.
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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

Top Skills

C/C++
Pandas
Python
R
Scikit-Learn

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