Sagar Mukherjee

Sagar Mukherjee is a Quantitative Researcher at BIT Capital, focusing on systematic trading strategies since January 2022. Prior experience includes roles as an Applied Scientist at Amazon, where Sagar developed automated data science pipelines and applied deep learning regression techniques. Sagar also worked at Morgan Stanley as an ML Quant, contributing to data analysis tools and reinforcement learning algorithms for recommender systems. At WorldQuant, Sagar achieved significant success with algorithmic trading models, ranking in the top 50 globally among 5,000 researchers. Earlier, Sagar served as an Associate Consultant at Capgemini, enhancing digitization efforts and pipeline automation. Sagar holds a Master’s degree in Financial Mathematics from the University of Luxembourg and a Bachelor’s degree in Mathematics and Computing from the Indian Institute of Technology, Kanpur.