Quantitative Researcher

About this role

ABOUT CUBIST 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. ROLE/RESPONSIBILITIES 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 REQUIREMENTS 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

Source listing: greenhouse_point72