About

Swapnil Parekh is a passionate machine learning researcher and practitioner with diverse experience working with top corporates, startups, and research labs on all facets of machine learning R&D. He is actively looking for ML/NLP opportunities, preferably at R&D divisions. Swapnil has won/finalized several hackathons and is an expert in Kaggle competitions. He has topped his class of 60 at the London School of Economics in a Master's Level course on ML taught by Prof. Kostas Kalogeropolous. Currently, Swapnil is working as a Data Scientist at Tata, where he performs EDA+ Data Cleaning + Statistics/Visualization for Big Ecommerce Data. He has worked on ML recommendation problems such as Next Basket Prediction with an Agile team using PySpark and SQL. He is familiar with Docker, MLFlow, Azure DataBricks. Swapnil has worked as a Software Development Intern at UBS, where he worked on Azure Migration of their flagship search product NEO. He researched solutions for Query Time joins which is not supported by Azure and developed and deployed synonym automation solution with 60% more efficient synonym maps. He has also worked as an AI Research Intern at Spherical Defence, where he implemented a Transformer based encoder for anomaly detection in network requests with Tests and achieved 99% accuracy on standard research datasets such as CSIC. Swapnil has a Bachelor's degree in Information Technology from Veermata Jijabai Technological Institute (VJTI) and is pursuing a Master's degree in Computer Engineering from New York University, which will be completed in 2023. He has also completed a course on Machine Learning in Practice from the London School of Economics and Political Science (LSE) and a course on High-Performance Computing Architectures and Algorithms in Big Data, AI, and Deep Learning sponsored by COE from the Indian Institute of Science (IISC). Swapnil's tech stack includes Research Scientist, Data Scientist, ML, Search, Azure, AI, SQL, Databricks, NLP, qa, Docker, Software Engineer, and Image Processing. He has 1.71 years of relevant experience.