Macro Quantitative Researcher
Point72New York, NY, United StatesHace 9 días
Tipo de contrato
- A tiempo completo
Descripción del trabajoDevelop 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 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
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
Desirable Candidates
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