• Assisted in building alert based trade monitoring system for Canadian Bank to identify patterns in trade execution failures • Contributed to MLOps architected library development using OOPs principles and unit testing that has reduced substantial efforts of Machine Learning model training, deployment, and data transformations • Deployed sophisticated data driven model using Commodity market, Futures and Geopolitical data that detects trade settlement errors and performed SHAP analysis to showcase relevant features and data-drift over the time • Curated memory optimized data pipeline for seamless transfer of traders' voice data using distributed computing and lazy evaluation chunking which process medium to big datasets (0.5TB to 1.5 TB) on 14GB multi-core CPUs and built prediction model to recognize emotions using fused Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM)

• Integrated highly optimized server-side Python API in lambda to compute implied volatility (IV), historical volatility (HV), future realized volatility (FRV) on fused historical and live streaming data sets of National Stock Exchange• Productionized real time market data streaming server using Kafka topics and distributed to downstream users that has serverd 25000+ clients concurrently with the data output 30 Mbps with zero downtime• Devised high throughput implied Volatility Adjustment model that yields volatility SMILE on noisy instruments data• Designed and implemented distributed computing module using MPI4py library for efficiently processing big data logs generated by options trading analytics platform• Delivered white label broker linking Derivative Trading product that allows users to trade on financial instruments• Coded low latency algorithm for computing top 10 gainers/losers using real-time volume-pricing data of around 100 stocks

Led a team of teaching assistants to successfully conduct experiments on Turbo machinery and Elementary fluid mechanics.

Organized various academic and extracurricular activities for Pg students of IIT Bombay.Managed department funds and looked after various extracurricular activities