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
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