Macro Quantitative Researcher
Point72 New York, NY
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Job Description
Role/Responsibilities
- Perform rigorous and innovative research to develop systematic signals for global macro (Futures, FX, etc.) markets
- Perform feature engineering with price-volume, order book and alternative data at intraday to daily horizons in high to mid frequency trading space
- Perform feature combination and monetization using various modeling techniques ranging from linear to machine learning models
- Manage 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
Requirements
- Develop systematic trading models across FX, commodities, fixed income, and equity markets
- Alpha idea generation, backtesting, and implementation
- Assist in building, maintenance, and continual improvement of production and trading environments
- Evaluate new datasets for alpha potential
- Improve existing strategies and portfolio optimization
- Execution monitoring
- Be a core contributor to growing the investment process and research infrastructure of the team
Desirable Candidates
- MS or PhD in physics, engineering, statistics, applied math, quantitative finance, or other quantitative fields with a strong foundation in statistics
- 2+ years of signal research experience in macro trading as part of a proprietary trading team
- Prior professional experience with feature engineering, modeling, or monetization
- Ability to efficiently format and manipulate large, raw data sources
- Demonstrated proficiency in Python, R, or C/C++. Familiarly with data science toolkits, such as scikit-learn, Pandas
- Strong command of foundations of applied and theoretical statistics, linear algebra, and machine learning techniques
- Collaborative mindset with strong independent research abilities
- Commitment to the highest ethical standards
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