About

Hemant Jain is a highly skilled Quantitative Strategist with almost 5 years of relevant experience in the finance industry. Currently working at a high frequency trading firm, Hemant's expertise lies in using advanced mathematical and statistical techniques to develop trading strategies that generate profits for the firm. Hemant's career began with an internship at Goedtech where he worked as a Content Developer, creating videos, notes, and questions on mathematical topics. After completing his Bachelor of Technology in Civil Engineering from the Indian Institute of Technology, Delhi in 2018, Hemant joined Citi as an Assistant Manager. Here, he investigated and implemented recent academic research to identify potentially profitable market inefficiencies, developed more than 20,000 profitable market-neutral signals for various global equity markets, and implemented a strategy to invest in Japan stocks that generated a PnL of around $150,000. Hemant was also the winner of the GAR of the Month competition for generating 2,204 paper trading alphas in the EU TOP250 universe and was awarded a Consolation Prize for having the strongest submission for the same competition. Hemant's technical skills include NLP, SQL, Python, and ML, and he has completed several machine learning projects, including implementing an NLP model to segregate stocks into various categories based on their 8-K reports and using linear regression and logistics regression models to categorize stocks based on their beta values, predicted values, and idiosyncratic volatility. With a strong background in research and a passion for using data to drive decision-making, Hemant is an asset to any organization looking to optimize their trading strategies.