About

Kunal Verma is a highly skilled and experienced machine learning professional with a strong background in research and development. He is currently working at Microsoft as a Senior Data & Applied Scientist, where he is responsible for developing and implementing machine learning models for various applications. Kunal has extensive experience in natural language processing (NLP) and deep learning, and has worked on several projects involving text classification, sentiment analysis, and language translation. He has also worked on developing custom BERT embeddings and end-to-end serving rest endpoints for NAICS (North American Industry Classification System) classifier, which is used to classify text-based descriptions from business public listings such as Yelp, Yellow pages, etc. Prior to joining Microsoft, Kunal worked as a Data Scientist III at Wells Fargo, where he developed a dynamic probabilistic delta-sensitive model over security for tape bidding price optimization (Bid-Tape) for mortgage trade desk. He also worked on developing clustering techniques for selecting pricing candidates for optimal price shift (+/-) in coherence with the probabilistic shift with varying market conditions and pricing strategies. Kunal also has experience working as a Product - Data professional at Tinyowl, where he was responsible for product analytics with insights from activity, acquisition, and transaction data to drive the roadmap features and business decisions. He also worked on data analysis, churn analysis, cohort-based funnel analysis, and experimental A/B testing setup in real-time for optimal product features. Kunal holds a Bachelor of Technology (B.Tech.) degree in Electrical and Electronics Engineering from the Indian Institute of Technology, Guwahati. He is skilled in a variety of technologies including Python, SQL, XGBoost, Keras, Spark, MySQL, and Azure. Kunal has 6.78 years of relevant experience and is a highly motivated and dedicated professional who is always looking for new challenges and opportunities to grow his skills and expertise.