May 2024 – Aug 2024 · 3 mos · Portland, Oregon Metropolitan Area · On-site

• Execution Trader: Mentored by head of trading to trade commodity spreads during the morning session. Made discretionary decisions on stop losses, price collars and alternate liquidity sources.
• Intraday Event Detection: Leveraged feature engineering framework to build signals that inform execution traders of price jumps, volatility and liquidity changes. One of the signals predicted price jumps in liquid energy futures with a 60% precision to significantly outperform the baseline autocorrelation model (52% precision)
• Feature Engineering: Engineered features using order book data of agricultural commodities to detect price limits 3 minutes to 30 seconds in advance. This resulted from a comprehensive stats module built on top of the forward curve library.
• Quantitative Development: Implemented rolling methods, price-adjustment methods, data structures in Python to create forward curves for outrights and spreads. This module was a core component of R&D codebase and was crucial for porting the tech stack to Python.

Jan 2023 – Jun 2023 · 5 mos

• Built a probabilistic pipeline in Python for generating mid-frequency strategies in the EQ Derivatives market (Index Options). The strategies were pushed to the live trading environment.
• Re-engineered an existing pipeline for exploring opportunities for mid-frequency trading in the FX derivatives and solved problems that resulted from the lesser frequency of trades ( relative to Index Options).

Dec 2021 – Jan 2023 · 1 yr 1 mo

• Developed an execution research framework in Python that helped scale up the Index options(NIFTY) portfolio.
• Developed an execution box ( C++) for SHFE, DCE, and ZCE commodities exchanges in China for overcoming limitations on order placement (cancellation and modification) which were crucial to he strategies.
• Streamlined the data processing for microstructure and snapshot data on the Indian Exchanges, significantly reducing the time required to train the models.

Aug 2021 – Dec 2021 · 4 mos · Pune, Maharashtra, India

• Developed pricing logic for non-standard bonds and computed risk measures like convexity and duration using the firm’s proprietary pricing toolkit, also wrote VBA scripts to test backsolving functions of the toolkit.
• Priced derivatives using numerical methods like Monte Carlo, Black-Scholes, and the Binomial model in VBA as a part of training.

Oct 2020 – May 2021 · 7 mos · Pune, Maharashtra, India

• Architectured a novel generative adversarial network to generate 3D objects with a limited proprietary dataset. Developed the machine learning framework using PyTorch, this also led to a publication in the IEEE’s conference on Artificial Intelligence and Machine Vision ( AIMV, 2021) . ( Check : https://ieeexplore.ieee.org/document/9670945 )

May 2020 – Jul 2020 · 2 mos · Pune, Maharashtra, India

• Worked on design and development of a Blockchain application . I was involved in the chaincode development in Golang, tokenisation of assets using ERC20 ,blockchain backend development in Golang and NodeJS , setting up CouchDB and writing rich queries for the same and private data collections on Hyperledger Fabric 2.0. Currently working on Kubernetes orchestration for the project.
• The Middleware fabric app pattern was used for for development.
• Technologies used : Hyperledger Fabric 2.0, Docker , CouchDB, Fabric CA , Kubernetes ,Fabric Node SDK

Sep 2019 – Sep 2020 · 1 yr · Pune Area, India

• Optimized an existing machine learning package (FETCH) to detect fast radio bursts in the data recorded by the GMRT radio telescope. Automated the entire pipeline of data preparation and machine learning using Python and bash scripts. The project was sponsored with ~ $ 3 million by NITI Aayog (India’s planning commission) for a scale-up.