Quantitative Developer

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. #J-18808-Ljbffr