In college, I spent weeks building my first back-test. The numbers were off, but I was hooked. That project sparked a deep interest in financial markets and scalable, data-driven systems that I have been pursuing ever since.
I graduated from BITS Pilani, India, in 2021 with a Bachelor's in Computer Science and a Master's in Economics. During undergrad, I explored different areas of finance, starting with digital payments at EY, then macro trading at Futures First, before discovering systematic investing during my internship at J.P. Morgan.
After graduation, I joined the Quantitative Investment Strategies (QIS) team at J.P. Morgan, where I spent four years building and managing systematic strategies across volatility, trend-following, cross-asset risk premia, and intraday signals. I worked closely with structurers and traders to automate workflows, support live risk management, and streamline strategy onboarding.
Currently pursuing the MSCF program at Carnegie Mellon, I am focused on deepening my understanding of quantitative finance and machine learning. I aim to work in quantitative research, building rigorous and adaptive investment strategies that solve real-world problems using data, mathematics, and technology.
