Design, train, validate, and deploy machine learning and deep learning models for e-procurement use cases including prediction, ranking, recommendations, entity resolution, document intelligence, and automation. Perform exploratory data analysis, feature engineering, experimentation, model evaluation, and error analysis. Build maintainable Python and SQL workflows, collaborate with engineering and product teams, and communicate technical findings to diverse stakeholders.

Lead product strategy and roadmap for Grainger's enterprise data platform. Partner with engineering, security, and product teams to define requirements, manage intake/triage, drive adoption, measure outcomes, and enable self-service data and MLOps capabilities. Prioritize platform initiatives, coordinate dependencies, and communicate changes via docs, demos, and workshops.