Graham Capital Management, L.P.
Graham Capital Management, L.P. is a privately held alternative investment manager that develops quantitative and discretionary global macro, trend-following, and multi-strategy programs for institutional and qualified investors. The firm manages approximately $20 billion in client assets and proprietary capital, earning management and performance fees. Founded in 1994 by Kenneth G. Tropin, Graham is headquartered in Rowayton, Connecticut, and serves global pensions, sovereign wealth funds, endowments, family offices, and advisors.
Open Positions at Graham Capital Management, L.P.
5 open positions
Develop and support business-critical trading technology applications for Graham Capital Management, with a focus on Windows client and server systems, pre-trade signals, and order generation. This junior-to-mid-level role offers opportunities to enhance existing systems and contribute to new software development.
Early-career developer supporting quantitative research and trading systems through hands-on development, refactoring, testing, troubleshooting, and maintenance. The role offers exposure to trading infrastructure, cloud computing, deployment processes, and collaboration with quantitative researchers and technology leaders.
Quantitative Research Developer responsible for building production trading signals and improving systematic futures and FX strategies. The role combines quantitative research, advanced programming, and close collaboration with investment and technology teams.
Build and enhance Windows and web applications supporting critical investment operations, including middle- and back-office processing, real-time pricing, and valuation. Join a small collaborative development team at Graham Capital Management and work across modern application technologies and financial workflows.
Join Graham Capital Management’s Data Science team to build production machine learning, forecasting, and data solutions that support quantitative research and trading. You’ll work with large financial datasets and cross-functional teams in a fully in-office role.