Summary
Shankar Sankararaman is a Senior Staff Data Scientist and AI architect with 8 years of experience designing production recommendation systems and scalable ML architectures at Intuit. He blends deep research pedigree—PhD-level expertise in uncertainty quantification and reliability from Vanderbilt and NASA-era applied research—with hands-on delivery of contextual bandits, reinforcement learning, and personalized marketing solutions that drove measurable business impact (e.g., a 1% login lift worth $9M and multi-fold CTR gains). At Intuit he built reusable packages and end-to-end pipelines (including an optimized Amazon Personalize deployment) and led cross-team standardization and executive-facing strategy. His background spans disaster-impact modeling, aerospace prognostics, and enterprise analytics at PwC, giving him a rare mix of rigorous probabilistic methods and product-focused ML engineering. Notably, he combines academic publication experience with practical leadership in growth, retention, and personalization for consumer finance products.
8 years of coding experience
13 years of employment as a software developer
Indian Institute of Technology Madras
Doctor of Philosophy (Ph.D.), Structural Engineering, Doctor of Philosophy (Ph.D.), Structural Engineering at Vanderbilt University
Masters' Graduate Certificate Program, Data Mining Graduate Program, Masters' Graduate Certificate Program, Data Mining Graduate Program at Stanford University
German, French, Hindi, Tamil