Subject Matter Expert (France) - Pharmaceutical Predictive Ordering & Regulatory Compliance
Job Description
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Provide deep pharmaceutical domain expertise to design a predictive, regulation-compliant pharmacy ordering model that:
- Reflects real-world pharmacy and wholesaler behaviour
- Embeds regulatory, ethical, and operational constraints
- Produces trusted, actionable outputs for pharmacists
- Balances margin, service level, and stock optimisation objectives
1. Predictive Ordering Domain Guidance
- Translate pharmacy and wholesaler operational realities into model constraints
- Validate demand drivers: seasonality, epidemiology, promotions, substitutions, shortages
- Define appropriate automation vs pharmacist control
- Ensure recommendations align with dispensing and supply realities
Ensure compliance with French and EU pharmaceutical regulations, including:
- Public Service Obligations (PSO)
- Controlled substances requirements
- Cold-chain constraints
- Generic substitution rules
- Ethical limits on promotion and inducement
- Ensure auditability, traceability, and explainability of recommendations
- Prevent legally or ethically non-compliant “optimal” outputs
- Review forecasts, predictive logic, and replenishment recommendations
- Challenge retail/FMCG assumptions unsuitable for pharma
- Stress test outputs against shortages, allocations, and regulatory limits
- Define KPIs relevant to pharmacists and wholesalers
Act as a bridge between: Data science, Product & UX, Pharmacy, wholesale, and supply chain stakeholders
Support workshops, design reviews, and decision forums.
Mandatory Experience
Pharmaceutical Domain (Non-Negotiable)
- 10+ years in pharmaceutical wholesale, pharmacy operations, supply chain, or demand planning
- Experience with independent and/or group pharmacies
- Experience with pharmaceutical wholesalers or short-line distributors
- Strong knowledge of French pharmaceutical market specifics
- Direct involvement in demand forecasting, automated/assisted ordering, stock optimisation, or replenishment algorithms
- Experience translating business logic into algorithmic rules (coding not required)
- Hands-on exposure to regulated decision systems
- Clear understanding of legal/ethical constraints on algorithmic decision-making in pharma
- ERP-driven ordering ecosystems
- Pharmacy-facing digital tools or B2B ordering platforms
- Sell-in / sell-out optimisation
- Large-scale transaction environments (tens/hundreds of thousands of daily order lines)
- Experience with explainable AI or regulated decision-support systems