Summary
Ram Narasimhan is a Principal Data Scientist with 14+ years of expertise applying mathematical optimization, operations research, and statistical analysis to decision-support systems—especially in airlines, airports, transportation and logistics. He has led data analytics groups and built mission-critical airline operations and scheduling solutions from algorithm design through production, and now focuses on shaping data to enable better downstream analysis. At GE (Digital and Vernova) and United Airlines he drove cross-domain analytics for IoT and transportation, and he also teaches practical data skills—using Python and R—in industry programs. He combines rigorous academic training (PhD in Operations Research/Industrial Engineering) with hands-on software and ETL experience, making him adept at turning constrained resource problems into deployable, actionable models. Notably, he balances production work with side projects and teaching materials on GitHub, signaling a continual curiosity for experimentation and knowledge sharing.
14 years of coding experience
20 years of employment as a software developer
Indian Institute of Technology Madras
Ph.D. Operations Research Industrial Engineering, Ph.D. Operations Research Industrial Engineering at University at Buffalo
University of California Santa Cruz