Quantitative Researcher

Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.

• →Perform rigorous and innovative research to discover systematic anomalies in global macro markets (futures, FX, etc.)
• →Perform feature engineering with price-volume, order book and alternative data at intraday to daily horizons in mid frequency trading space
• →Perform feature combination and monetization using various modeling techniques
• →Manage the research pipeline end-to-end, including signal idea generation, data processing, modeling, strategy backtesting, and production implementation
• →Maintain and improve portfolio trading in a production environment
• →Contribute to the analysis framework for scalable research

• Background in mathematics, statistics, machine learning, computer science, engineering, quantitative finance, or economics
• 2-6 years of signal research experience in macro trading as part of a trading team
• Specialization in swaps, fixed income, or commodities trading a plus.
• 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