Build, deploy, monitor, and retrain machine learning models for ETA forecasting, status extraction, and logistics automation. Develop regression, classification, time-series, NLP, and LLM-based solutions using noisy supply chain data. Own production ML pipelines, diagnose offline-to-live performance gaps, and measure business impact. Collaborate with product, engineering, and operations teams while mentoring data scientists and making architecture and build-versus-buy decisions.

Build, deploy, monitor, and retrain machine learning models for ETA forecasting and message-based logistics status extraction. Own end-to-end production ML pipelines using noisy supply chain data, diagnose offline-versus-live performance gaps, and automate manual processes. Collaborate with product, engineering, and operations teams, translate model improvements into business value, make architecture tradeoffs, and mentor data scientists and engineers. Work includes NLP/LLM extraction, Airflow orchestration, Grafana observability, and scalable model deployment.