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Point72

Microstructure Quantitative Researcher

LocationNew York, NY, New York
Work modeon-site
Typefull-time
DepartmentQuant Management
Company size1,001–5,000 people
First seen5mo ago
Last seen23h ago
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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