Mehrdad Shahabi is a Principal Data Scientist with eight years of experience building production-grade ML systems and leading teams across automotive, e-commerce, and finance domains. He combines a PhD-trained background in operations research and transportation optimization with hands-on expertise deploying models at scale on Azure and AWS, including telemetry-driven drivability prediction and fraud detection pipelines. Known for pragmatic cloud strategy adoption of LLMs and tooling like MLflow and SageMaker, he bridges research-grade optimization with product-focused delivery. His career spans industry leaders (Walmart Global Tech, GM Financial, Amazon, Ford) and academia, where he developed large-scale online allocation and ride-sharing optimization—an uncommon mix that helps him turn complex nonlinear problems into deployable solutions.
8 years of coding experience
14 years of employment as a software developer
Doctor of Philosophy (PhD) Transportation Engineering(Emphasis on Operations Research), Doctor of Philosophy (PhD) Transportation Engineering(Emphasis on Operations Research) at West Virginia University
Contributions:4 commits, 2 pushes, 2 branches in 22 days
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