Nilay Tiwari
Class of 2027
Bio
"How do you price uncertainty itself?"
That question has driven my five-year journey across global options markets and cutting-edge generative AI.
As a volatility trader and quantitative strategist at a leading high-frequency trading firm in India, I built and scaled systematic options strategies across the U.S. and India. My work combined real-time execution, statistical arbitrage, and volatility modeling, delivering high Sharpe strategies deployed at scale. Now, as an MSCF candidate at Carnegie Mellon, I'm focused on rethinking derivative pricing using generative models, applying deep learning to price contracts in a more flexible, data-driven way.
I bring deep domain expertise in options, low-latency coding experience in C++, strong data analysis skills in Python and R, and a solid foundation in mathematics and stochastic calculus. I also have a proven record of building scalable trading strategies in global financial markets. I'm looking to join a research-driven hedge fund or prop desk where I can apply these skills to solve hard problems in volatility and quantitative trading.
I'd be glad to connect over Zoom or in person to show how I can contribute from day one.