About

Sankalp Mule is a highly skilled Quantitative Analyst at Wells Fargo with over a year of relevant experience. He is an alumnus of the prestigious Indian Institute of Technology Bombay, where he pursued a Master of Technology degree in Machine Learning and Data Science. He also holds a Bachelor of Technology in Material Science from the same institution. Sankalp is a seasoned researcher in the field of Data Science, Machine Learning, and AI. He has a deep understanding of Predictive Maintenance (PdM) and is currently working on a Bank of Baroda project aimed at formulating a PdM model for ATMs. His focus is on predicting whether an ATM will fail in the near future, enabling advance scheduling of corrective maintenance to prevent unexpected equipment breakdowns and improve asset reliability for customers. Sankalp's work on this project is geared towards reducing additional operational costs caused by over-maintenance. Sankalp has also worked as a Machine Learning Intern at Edunomics Tech Solutions, where he developed a document summarizing tool, a Covid-19 diagnosis chatbot, and an AI-based career mentoring smart bot. He implemented the backend in Flask and managed the database in MongoDB for primary-stage data collection. As a Department Academic Mentor at the Indian Institute of Technology Bombay, Sankalp provided academic refinement and time management counseling to six sophomores to boost their scholastic performance. He was appointed to help academically underperforming students enhance their scholastic performance and ensure overall well-being. Sankalp's tech stack includes Deep Learning, AI, Research Scientist, Data Scientist, ML, Flask, Backend, NLP, ReactJS, MongoDB, Frontend, and Web. He is a highly motivated individual with a passion for using his skills to solve real-world problems.