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