Leading a dynamic team at Amazon Business, I oversee the central engineering, science, product, and operations efforts focused on developing advanced products and services to detect and prevent abusive behavior on our platform. Our mission is to protect the integrity of Amazon Business, ensuring a fair and secure environment for legitimate businesses in an ever-evolving digital landscape.Our multidisciplinary team, composed of experts in engineering, data science, and product development, collaborates to create cutting-edge, data-driven solutions that block abusive activities. By staying ahead of emerging threats, we ensure that real businesses can thrive without the disruptions caused by abusive actors.

In my role as an Engineering Leader at Consumer Behavior Analytics team, I spearheaded the development of a generic platform for building machine learning models using Spark(Scala). This project involved working closely with the Consumer Marketing Analytics team to enhance our customer forecasting model building and scoring platforms, ultimately improving the scalability and efficiency of our big data platform.

Led the development of an AWS pricing plan simulation platform that significantly reduced pricing errors previously made by program managers. This innovative solution safeguarded against costly mistakes, preventing potential losses amounting to millions of dollars and ensuring greater accuracy and reliability in pricing strategies.

As an SDE 2 at Amazon in Bengaluru, India, I contributed to the Selection Monitoring team by designing and implementing a platform for training deep learning models tailored for Auto Scraping. I developed advanced deep learning models to automate the scraping of product web pages, enhanced machine learning models for item categorization, and streamlined the item categorization process through automated pipelines, driving efficiency and scalability.

As an SDE in Bing's Knowledge Graph team (Satori), I developed and optimized entity matching models across key segments, including movies, actors, and music directors. These models effectively identified similar entities from diverse sources such as Wikipedia, IMDb, and Firebase, contributing to the enhancement of Bing's Knowledge Graph by deduplicating data and enriching information accuracy and completeness.

Worked as a Software Developer in the Cash Equities IT department at Credit Suisse, contributing to one of the premier Advanced Execution Engine products. My primary responsibilities included building robust API integrations to fetch real-time stock trading information from leading data providers, Reuters and Bloomberg, and seamlessly delivering this data to the trading desk to support informed decision-making.

Research Interests: Machine learning and its applications Graduate seminar topic : Achieving Sparsity in Principal Component Analysis: A Review of Methods. (under Prof. J.Saketha Nath)As part of Seminar studied different types of PCA to understand fundamentals of PCA and advance techniques related to PCA. I studied about PCA, sparse PCA, kernel PCA and Structured Sparse PCA.Graduate Thesis: OCR for printed Telugu documents. (under Prof. J.Saketha Nath)Created OCR application for Telugu printed documents implemented/experimented some techniques for different stages of OCR like binarization, noise removal, segmentation and classification. Created OCR for Telugu printed documents without images.

Worked in the Banking and Financial Services vertical at Cognizant Technology Solutions, where I contributed to key projects for a private bank. I developed a Mutual Fund Automation system and streamlined the New Account Setup process through automation. Additionally, I designed and implemented financial reports using Jaspersoft, quickly upskilling to replace costly legacy Crystal Reports, reducing operational expenses and enhancing reporting efficiency.