About

Indranil Das is an Innovation Leader and Architect of Advanced Analytics Research Lab with over 19 years of relevant experience in the field of Data Science, Data Engineering, and AI. He is currently working as a Data Science Engineering Manager in the Ent Analytics and Data Science (EADS) division of Wells Fargo. In his current role, he is responsible for driving the Data Science practice and establishing an end-to-end workflow from Proof of Concept to MDLC to Model Monitoring in a regulatory setup. Indranil's expertise lies in building world-class on-premise Research Labs with necessary security controls to work with Production, Confidential, and Sensitive Data. He has a proven track record of driving corporate vision and strategy of AI-Center Of Excellence to enable Data Science Practice, Big Data Engineering prototypes, across all Lines of Business. He has also developed Spark Frameworks for code reusability and has expertise in Cloudera-Hortonworks platform underlying architecture. Indranil has a Master's degree in Data Analytics from Georgia Institute of Technology and a Bachelor's degree in B. Tech from IIT Dhanbad. He has worked with companies like DXC Technology and Hewlett Packard in the past, where he was responsible for defining solution architecture, implementing data-driven insights, and developing leads and opportunity reports for ranked critical accounts. Indranil has a keen interest in Research Potential and has worked on projects related to Deep Learning, Invariant Risk Minimization, Fairness, and Bias. He has also been involved in Climate Science Research and has partnered with the University of Maryland to develop a framework to understand scenarios and interpret the results. Indranil is proficient in Big Data Hadoop, Open Source Research, Python, Pyspark, R, SAS, Distributed compute, Spark, H2O, Data Robot, Feature Store, Reusable framework for data ingestion, and visualization for accelerated research and data insights. He has also worked on ASP.net, Webservices, node.js, Vertica cloud infrastructure, SQL Server, and QlikView dashboards.