Quantitative Analyst/Data Scientist

Passionate about investments, I specialize in infusing quantitative rigor into qualitative narratives and hypotheses, consistently achieving exceptional results in financial markets. My journey began with an engineering degree from the Indian Institute of Technology, where I developed a strong foundation in technical problem-solving. Building on this, I earned the FRM certification and am currently pursuing a Masters in Finance at the London Business School to further expand my expertise. During my five-year tenure at Fidelity Investments, I played a pivotal role in conceptualizing and designing innovative systematic investment products, conducted extensive research on investment frameworks, and crafted effective risk management strategies. These products, often pioneering in the market, allowed me to live out my passion for helping clients achieve their investment goals. Engaging in diverse projects, I honed my skills in non-linear optimization, derivatives and hedging, statistical and actuarial modeling, and machine learning. On a personal note, my active interest in systematic investment strategies has led me to explore momentum and statistical arbitrage strategies in equities and commodities, implementing risk-based allocation schemes. I am also dedicated to bridging the realms of artificial intelligence and investment management. My research, available on my GitHub repo, delves into portfolio allocation strategies using reinforcement learning and the use of neural networks to identify momentum regimes in commodities, yielding encouraging results.