UK remote
AI / ML Quantitative Research Manager
About this role
Graham Capital Management, L.P. (collectively with its affiliates, "Graham") is an alternative investment manager founded in 1994 by Kenneth G. Tropin. Specializing in discretionary and quantitative macro strategies, Graham is dedicated to delivering strong, uncorrelated returns across a wide range of market environments. As one of the industry’s longest-standing global macro and trend-following managers, Graham remains committed to innovation, evolving its strategies through a robust investment, technology, and operational infrastructure.
Graham harnesses the synergies between its discretionary and quantitative trading businesses to offer a broad suite of complementary alpha strategies, each built on the principles of thoughtful portfolio construction, active risk management, and diversification by design. Graham invests significant proprietary capital alongside its clients – including global institutions, endowments, foundations, family offices, sovereign wealth funds, investment management advisors, and qualified individual investors – reinforcing alignment of interests across all strategies.
The foundation of Graham’s sustainability and success is the experience and contributions of its people. The firm seeks to cultivate talent, encourage the diversity of ideas, and respect the contributions of all. In turn, each employee shares in the responsibility of strengthening those around them. Description Graham Capital Management, L.P. is seeking an AI/ML Quantitative Research Manager to join our Quantitative Strategies team and lead collaborative AI/ML team research efforts.
This individual will report into and work closely with our Chief Investment Officer of Quantitative Strategies to assess existing AI/ML capabilities, define a research agenda to improve AI/ML capabilities in current systematic trading systems, and create new AI/ML trading signals to complement and diversify the firm’s main strategies. The individual will maximize performance and competitiveness by utilizing advanced methods in quantitative analysis, risk management and portfolio optimization.