Summary
Tejash Shah is a Senior Applied Machine Learning Scientist with 8 years of experience building end-to-end NLP and ML solutions that move projects from prototype to production at Grainger and J.D. Power. He has deep expertise in semantic product matching, extreme multi-label text classification, and large-scale ETL (400M+ records) using Spark/Presto and modern cloud data warehouses. Comfortable across the stack, he deploys models with Flask, Docker, Kubernetes and automates CI/CD with GitHub Actions while monitoring production with Datadog and Splunk. His work has materially reduced manual labeling and improved recall in NLP pipelines, and he pairs model interpretability tools (SHAP, PDP, ELI5) with executive-facing dashboards to drive business decisions. Holding an M.S. in Electrical Engineering from San Jose State, he combines hands-on engineering with a continuous-learning mindset and a knack for turning messy, large-scale data into practical, revenue-driving products.
8 years of coding experience
4 years of employment as a software developer
San José State University
Bachelor’s Degree, Electronics and telecommunication Engineering, Bachelor’s Degree, Electronics and telecommunication Engineering at IET - DAVV
English, Hindi, Gujarati