Sujit Khanna

Sujit Khanna is a seasoned quantitative researcher with extensive experience in the financial and digital asset sectors. Currently leading quantitative research initiatives in the digital assets space at Cross River since March 2022, Sujit has previously developed and deployed high and mid-frequency trading strategies at Apifiny. Sujit's career includes a data science internship at Tesla, where algorithmic trading strategies were created for the electricity markets, and roles at Edelweiss Financial Services and Morgan Stanley, focusing on algorithmic trading and quantitative analysis of global equity futures and derivatives. Sujit began a career in finance at Barclays Investment Bank as a market risk analyst and has also contributed to quantitative analysis during a summer internship at Karvy Capital. Educational qualifications include a Master's degree in Computer Science from the Rochester Institute of Technology, an MBA in Capital Markets from NMIMS, and a Bachelor of Engineering in Electrical, Electronics and Communications Engineering from the University of Mumbai.