About

Apoorv Khare is a highly skilled and experienced data scientist with expertise in sentiment analysis, AWS, RNN, and Spring. He is currently working as a Freelance Data Scientist at redseer, where he has scraped Twitter, Facebook, Instagram, and brand-specific websites to obtain the Voice of Customer for 5 major beauty brands. Apoorv has carried out analysis over the brands Ulta Beauty, Sephora, Purplle, Health & Glow, and Nykaa, and executed sentiment analysis and opinion mining to infer the customer satisfaction trend over geographical location and timeline. He has also deployed a Quasi-RNN, trained on Amazon’s product review data (Kaggle), for predicting sentiment, aided by NLTK and TextBlob. In the past, Apoorv has worked as a Full-stack Developer Intern at Dataphi Labs, where he worked on developing an Enterprise mobility software with features such as Push Notifications, Role-Based Access, and customized user workflow. He has also worked as a Project Leader at Information Management Group, IIT Roorkee, where he was responsible for the development and maintenance of internet and intranet applications in the institute, including the website of IIT Roorkee. Apoorv has a Bachelor's degree in Civil Engineering from DOMS, IIT Roorkee, which he completed in 2020. He has a wealth of experience in various technologies such as Java, Django, Docker, Javascript, Postgres, Web, Software Engineer, PHP, MySQL, Microservices, Flask, Azure, GCP, Backend, and Golang. With 8.11 years of relevant experience, Apoorv is a highly skilled and motivated data scientist who is passionate about delivering high-quality results to his clients.