Summary
Saket Garodia is a Senior Data Scientist based in the San Francisco Bay Area with 6+ years of experience building end-to-end ML and AI solutions for large-scale retail and consumer businesses. He currently drives personalization and loyalty initiatives for Kroger’s digital and e-commerce teams at 84.51˚, and previously delivered customer retention, NLP-driven sales optimization, and productionized ML pipelines at Asurion and other firms. Trained in computer science and business (MS in Business Analytics, MBA, and online ML coursework at Stanford), he blends strong quantitative modeling with product-minded deployment skills across AWS, Docker, and SQL ecosystems. Saket’s work spans supervised and unsupervised methods, deep learning for text, and practical feature engineering that has translated into measurable business impact (e.g., improved sales and reduced defaults). He also shares technical insights publicly via Medium and focuses on agentic LLM applications and shipping ML products end-to-end.
6 years of coding experience
5 years of employment as a software developer
Master of Science - MS, Business Analytics (Data Science), GPA - 4.0/4.0, Master of Science - MS, Business Analytics (Data Science), GPA - 4.0/4.0 at University of Cincinnati Carl H. Lindner College of Business
Master of Business Administration - MBA, International Business, Master of Business Administration - MBA, International Business at Rennes School of Business
Master of Business Administration (M.B.A.), International Business, Master of Business Administration (M.B.A.), International Business at Indian Institute of Foreign Trade
Bachelor of Technology (BTech), Computer Science and Engineering, 8.02/10, Bachelor of Technology (BTech), Computer Science and Engineering, 8.02/10 at National Institute of Technology Calicut
Machine Learning (Online Certification), Machine Learning (Online Certification) at Stanford University
English, Hindi, French