Python Developer, Trading Research

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

• Dynamically managing portfolio risk by evaluating historical and real-time strategy performance.
• Overseeing automated trade execution and monitoring transaction costs.
• Supervising a small team of researchers and developers on a daily basis.
• Designing, researching, and managing sophisticated investment strategies by creating and engineering advanced quantitative financial computer modeling systems to aid in analysis and research.
• Performing research to acquire historical and production data sources needed to build investment models.
• Designing and developing quantitative mathematical algorithms to link diverse data sets from various providers.
• Engineering investment models that will make buy and sell recommendations for the portfolios using advanced quantitative mathematics, statistics, and investment theory to forecast risk, return, and trading costs.
• Using quantitative models to value securities.
• Conducting ongoing, cutting-edge quantitative research and analysis to enhance existing strategies and to expand into new markets.
• Developing aspects of successful statistical models, focusing on forecasting and optimization.
• Expanding trading universe and volume, and expanding to other exchanges and products.

Requirements

• Advanced degree (Master’s or Ph.D.) in a computational or analytical field.
• Minimum of 10 years of experience developing, researching or implementing quantitative models for equities, futures and/or FX.
• Hands‑on experience with all aspects of the research process, including methodology, data collection and analysis, testing, prototyping, backtesting, and performance monitoring.
• Innovative, intellectually driven, with an intense curiosity about financial markets and human behavior.