Graham Capital Management, L.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. P. is seeking a ML Engineer to join our Data Science team, a future-looking technical arm of Graham Capital. The Data Science department straddles traditional Data Science and Engineering roles as well as the application of Machine Learning & AI. Every day we work to transform our business through data, technology, and the insights we provide our stakeholders. At Graham Capital, our systems feed live models around the clock, span billions of market data ticks, an ever-increasing corpus of news and other texts as well as a broad spectrum of financial and alternative data. You will be part of a growing team within Data Science. You will work alongside world-class talent to find innovative solutions to some of the most interesting problems on the buy-side. You will work closely with other areas such as Technology, Quantitative Research and Portfolio Manager groups as well as Risk and Operations to learn about problems they face with respect to data and ultimately develop cutting edge solutions. Your focus will be to dive deep into multiple data sets to understand relationships, develop time series, forecasting models, and support quant strategies, and provide new insights and leverage state-of-the-art machine learning and advanced statistical methods to produce the best data sources for the fund. Undergraduate or higher degree in Computer Science, Engineering, Operations Research, or other quantitative discipline ~3+ years of hands-on experience with Machine Learning and Statistics on large, unstructured, data sets ~ Experience writing production code for multi-client systems serving model results is a great plus ~ Full-stack experience with Python (preferred) or C++, Spark/Scala, SQL or other distributed data processing technologies as well as experience working comfortably building and deploying services and models in containerized environments ~ Experience with scientific computing, statistics, optimization, time series, panel data, etc. ~ Comfortable handling multiple projects to solve varied problems working with multiple teams ~ This role requires commuting into our London office Mondays through Fridays.
Machine Learning Engineer - Hybrid Remote in London employer: Graham Capital Management
Graham Capital Management, L.P. is an exceptional employer that fosters a culture of innovation and collaboration within its Data Science team. Located in the heart of London, employees benefit from a dynamic work environment that encourages professional growth through exposure to cutting-edge machine learning applications and close collaboration with industry experts. With a strong commitment to diversity and employee development, Graham offers a unique opportunity for individuals to contribute meaningfully while advancing their careers in a supportive and forward-thinking organisation.
