Experience

These are a few recent highlighted experiences. For more details, check out my CV.

National Stock Exchange, Mumbai, India

• Position: Quantitative Finance Summer Intern
• Impact: Closely worked with the Fixed Income Analytics team of NSE to develop an attribution system directly competing with industry solutions, implemented new frameworks and a variety of attribution models for fixed income markets specifically calibrated on Indian sovereign and corporate bond data, employed machine learning for modeling the yield curve in python and pipelined output for excel.
• Duration: 4 months (Apr-Aug 2020)
• Mentors: Aman Singhania, Mukesh Agarwal
• Links: Offer Letter

RAFA AI, Palo Alto, California - Remote

• Position: Quant Research and Development
• Impact: Ongoing, working in an end-to-end startup framework, directly responsible for pushing important deep learning and quantitative product releases on www.rafa.ai.
• Duration: May 1, 2020 - current
• Mentors: Abhinav Sinha, Siddharth Raisoni
• Links: Offer Letter

Indian Statistical Institute, Calcutta, India

• Position: Research Intern
• Impact: Modeled the financial trading task as a Markov decision process, developed novel definitions of the state, action and reward spaces for deep reinforcement learning usecases, demonstrated alpha generation in dynamic markets including from crude oil, equity and foreign exchange, let to a publication accepted at the 9th India Finance Conference, IIM-A.
• Duration: 3 months (May-Aug 2019)
• Mentor: Dr. Subhamoy Maitra
• Links: Letter of recommendation

National University of Singapore, Singapore

• Position: Academic Intern, Remote research intern
• Impact: Ranked 15 (out of 100+ students) in an academic internship under the Global Academic Internship Program (GAIP); tools like Hadoop, MapReduce (for Data Storage) and Python, R, Excel (and various libraries) for Data Exploration and Analysis were used on various real-world data sets ranging from images to text; after completion, worked as a remote research intern, focusing on sentiment analysis specifically on technical news or reviews and mapping this sentiment to predict future performance of the product.
• Duration: 3 weeks on site, 6 months remote (Jun 18 - Jan 2019)
• Mentor: Dr. Tan Wee Kek
• Links: Certification