Data Product Manager Pharma Manufacturing & Supply Chain

Data Product Manager Pharma Manufacturing & Supply Chain (Remote | Contract or Permanent | Occasional Site Visits) About the role (short): We're hiring a pragmatic, product-minded Data Product Manager to lead AI-driven data products that improve manufacturing consistency (recipes/formulations), yield and supply-chain resilience across pharmaceutical manufacturing. Remote-first, occasional visits to client sites. Open to contract or permanent candidates with strong pharma manufacturing experience. What you'll own Define, build and run data products that use AI/ML to optimise manufacturing recipes, batch consistency and supply-chain decisioning. Translate operational problems (variation, deviation, OEE, out-of-spec batches, shortage risk) into measurable data product outcomes. Partner with Manufacturing, Quality, Regulatory, Supply Chain, IT/OT and Data Science to prioritise, scope and deliver features. Own product lifecycle: discovery, requirements, MVP, validation, deployment, monitoring and continuous improvement. Ensure solutions meet GxP, GMP and regulatory audit requirements (data lineage, explainability, versioning). Drive data product KPIs: batch yield, variance reduction, time-to-release, forecast accuracy, inventory turns. Work with engineering to embed MLOps, model validation, and robust monitoring into production pipelines (edge/cloud/hybrid). Evangelise adoption; design stakeholder training and change management for shop-floor & supply-chain teams. Must-have (non-negotiable) 5+ years product management experience delivering data/AI products (end-to-end). 5+ years' experience in pharmaceutical manufacturing or closely related regulated CPG/FMCG production (formulation, batch processes, aseptic, continuous). Clear understanding of GMP/GxP, batch records, quality control workflows and regulatory constraints. Hands-on familiarity with manufacturing systems: MES, LIMS, SCADA, PLC/OT data, OPC UA, and ERP (SAP preferred). Practical knowledge of AI/ML capabilities and limitations in production (predictive quality, anomaly detection, digital twins, federated learning). Strong stakeholder skills - you can lead technical and non-technical teams, and influence senior execs. Excellent product discovery and problem-framing skills (user research, experiments, A/B where applicable). Proven track record taking models from prototype to validated production (including model governance & explainability). English fluent; ability to travel to client sites occasionally. Nice-to-have Experience with MLOps, model validation frameworks (MLflow, Seldon, TFX). Background in supply chain analytics (demand forecasting, S&OP, inventory optimisation). Experience with process analytical technology (PAT), Design of Experiments (DoE) or continuous manufacturing. Regulatory audit experience involving data/ML systems. MSc/PhD in data science, engineering, pharma science or similar. *Rates depend on experience and client requirements