Summary
Alexander Remizov is a senior quantitative researcher and trader with 11 years of experience and over 8 years focused on systematic credit strategies across US and European markets. He has built and productionized statistical and machine-learning models for corporate bond market making and credit ETFs at Goldman Sachs, DRW, and now Man AHL, combining rigorous backtesting with real-time algo monitoring and risk adjustments. Trained in applied mathematics, physics and economics (MIPT and New Economic School), he brings a strong numerical-PDE and simulation background from early aerospace research to inform robust model design. Known for turning complex data signals into deployable alpha and for recalibrating models to shifting market regimes, he blends research depth with hands-on engineering. Based in the UK, he pairs a trader’s instincts with research discipline and a taste for elegant, sometimes paradoxical thinking hinted at in his playful GitHub bio.
11 years of coding experience
5 years of employment as a software developer
Bachelor of Science (B.S.) Master of Science (M.S.) Applied Mathematics and Physics, Bachelor of Science (B.S.) Master of Science (M.S.) Applied Mathematics and Physics at Moscow Institute of Physics and Technology (State University) (MIPT)
Master of Arts (MA) Economics, Master of Arts (MA) Economics at New Economic School
English, Russian