Senior Manager, Supply Chain Data Analytics & Governance

Significant experience owning master data and data governance for at least one major domain (e.g., parts/SKUs, suppliers, locations, BoMs), including standards, stewardship processes, and data-quality metrics. 8–10+ years in data, analytics, or data science roles, including 4–5+ years working with supply chain, operations, manufacturing, or other complex networked systems. 3+ years managing multi-disciplinary data teams (e.g., data engineers, analysts, data scientists, or similar) in a product, platform, or analytics context. Proven track record of defining and executing a data/analytics strategy for a business function including roadmap definition, prioritization, and delivery of measurable business outcomes. Experience partnering with a central IT / Data & AI organization on ingestion, transformation, and modeling. Familiarity with delivering machine learning and/or AI-powered solutions (e.g., forecasting, optimization, anomaly detection, LLM/agent-based workflows) into production environments with appropriate controls and monitoring. Strong SQL skills (ideally with experience on Postgres or similar) and fluency in at least one analytics programming language (e.g., Python). Experience with modern cloud data stacks, including columnar analytical databases or data lakes and ELT tools and patterns.

Set and maintain the supply chain data strategy and roadmap across MDM, analytics, data science, and AI agents. Design and run the supply-chain data and master-data governance model, including standards, stewardship, and issue management. Collaborate with the Data & AI team in IT on ingestion, modeling, and tooling. Identify and deliver high-value analytics and AI/agent use cases that improve visibility, decision speed, and predictability across the supply chain.