Working with the Demand Forecasting Team at Walmart
Currently working on developing a forecasting algorithm to predict the annual omni-channel sales of items.
This solution will assist Planners in determining purchase quantities and support the Assortment team in making assortment decisions for the upcoming year.
Machine Learning Researcher Intern
TrustLab
January 2024 - April 2024
Developing Trust & Safety systems that leverage LLMs and NLP methodologies to effectively identify and filter high-harm
content, such as misinformation, hate speech etc.
Machine Learning Engineer Intern
Walmart AI labs
May 2023 - August 2023
Worked with the Central Demand Forecasting team of Sam’s Club.
Implemented and fine-tuned a Transformer model for Demand Forecasting using Time Series Data of the Sam’s Club Sales.
The model was trained on a dataset with millions of records.
Achieved a 17% improvement over the current ML model that is used by Sam’s Club for forecasting sales. The
transformer’s forecasts were 15% better than the current ML model for sales during holiday periods and for items with
high variance in sales. This improvement in forecast can impact sales worth over 16 billion USD.
Used data parallelization techniques to reduce the training time. Proposed a concrete plan for deploying the model in
production.
Selected as one of the top 3 intern projects to be presented to the CTO of Sam’s Club.
CS6422 - Database System Implementations (Fall'22, Fall'23)
CS8803 - Advanced Database System Implementations (Spring'23)
Software Development Engineer
Wells Fargo
July 2021- July 2022
Developed APIs that provide traders and users with Equity Derivatives data.
Built data pipelines for transformation and storage of raw data obtained from vendors.
Led the initiative to enhance various ETL jobs by adding recovery measures to ensure reliable
receipt of Equity Derivatives data. This significantly reduced the job failures.
Played a key role in resolving the issues of the Equity Derivatives applications in Production.
Tech Stack: Java, Oracle, Spring Boot, Cucumber BDD
Software Engineering Intern
Google India
May 2020 - July 2020
Applied Natural Language Processing and Natural Language Generation techniques for Reviews Moderation in Google Maps.
Explored Review Generation using different NLG models like LSTM, VAE and GAN and built a reviews generator with a high BLEU score.
Developed a classifier with high Precision score using NLP classification algorithms.
Analyzed the model predictions using AI Explainability tools like LIME to improve the performance of the models.