About

Shubhmay Potdar is an experienced Data Scientist with a strong background in Machine Learning, Deep Learning, Natural Language Processing, Data Engineering, and Big Data Analysis. With over 9 years of experience in the analytics domain, Shubhmay has built products for advanced data analytics and solved complex problems in the supply chain domain, such as demand forecasting, stock out predictions, lead time predictions, and supplier ranking. Currently, Shubhmay is the Manager of Data Science at Aera Technology, where he leads a team to build a distributed AutoML system featuring boosting algorithms, bagging algorithms, and neural nets. He also leads the effort to build an MLOps platform on Kubernetes to deploy ML pipelines with features including automated deployment, environment management, model monitoring, drift detection, and AB testing. Shubhmay is also working on a research project to apply Reinforcement Learning to optimize Inventory Management in Multi-Echelon Supply Chain. He is currently enrolled in the graduate program in Computer Science with specialization in Machine Learning at Georgia Institute of Technology, Atlanta. Shubhmay is interested in the application of AI in healthcare, especially in drug discovery, and wishes to pursue research in the same domain. Before joining Aera Technology, Shubhmay worked as an Assistant Vice President - Data Scientist at Barclays and a Senior Software Engineer at EQ Technologic. He holds a Bachelor of Engineering degree in Computer Engineering from Vishwakarma Institute of Technology and is expected to complete his Online Master of Science degree in Computer Science with specialization in Machine Learning from Georgia Institute of Technology in 2022. Shubhmay is a skilled Data Scientist, Research Scientist, and Software Engineer with expertise in Kubernetes, Reinforcement Learning, AI, NLP, and other relevant technologies. He has 7.43 years of relevant experience and is passionate about using his skills and knowledge to solve complex problems and build innovative solutions.