Quantitative Researcher for Systematic Strategies (New York or Chicago)

Our client is one of the world’s premier investment firms. The firm deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures, credit, 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 Quantitative Researcher for a new team focused on systematic corporate bond and credit derivatives strategies. Role/Responsibilities: Independently conduct quantitative research, adopting a rigorous approach and using statistical and structural models. Contribute to all aspects of the research and production process, including implementation of fitting tools; data organization; generation of alphas, risk and TC models; P&L attribution, etc. Proactively search for and prioritize new ideas and datasets for alpha potential. Contribute to continuous improvement of the investment process and infrastructure in collaboration with the portfolio managers, developers and traders on the team. Requirements: PhD or Master’s degree in Economics, Finance, Statistics, Mathematics, Physics, or other quantitative discipline. 2+ years of experience developing statistical and fundamental alpha signals, risk factors for single name credit, equities, or options. Demonstrated ability to conduct research utilizing large data sets. Experience with FICC, credit or option pricing models is preferred. Experience with numerical optimization methods is a plus. Solid programming skills: understanding of the object-oriented programming and CI/CD framework. Proficiency in Python, including with packages used for data research, best practices of coding style, etc. Strong communication skills. Willingness to take ownership of his/her work, working both independently and within a team. #J-18808-Ljbffr HRB