RGM Analytics Lead

Job Title

RGM Analytics Lead

Ready to shape the future of commercial decision-making at Philips? In this role, you will help drive profitable growth in Personal Health by combining Revenue Growth Management, commercial strategy, data science, and AI-enabled decision support.

You will lead analytics for key RGM levers including pricing, price-pack architecture, pocket price waterfall / gross-to-net, promotions, trade spend, portfolio mix, bundling, and retailer sell-in pricing. The role sits at the intersection of business and analytics: turning consumer, shopper, retailer, competitor, and financial data into recommendations that improve price realization, margin, promotion ROI, and growth.

It is an RGM leadership role with a strong data, AI, and analytics angle. You will be expected to frame the right commercial questions, work closely with Data Science, Analytics, IT, Sales, Marketing, and Finance teams, validate model outputs, and embed data-enabled recommendations into practical business workflows.

• Own and drive the end-to-end RGM analytics agenda across pricing, price-pack architecture, promotions, trade spend, portfolio mix, bundling, and retailer sell-in pricing.
• Build transparent pocket price waterfall / gross-to-net views across list price, invoice price, discounts, rebates, trade terms, promo funding, net price, and margin.
• Shape product pricing strategies, price ladders, price-pack architecture, channel packs, retailer-exclusive offers, and bundling opportunities for Personal Health categories.
• Use advanced analytics and AI/ML techniques to improve pricing decisions, demand forecasting, price elasticity understanding, promotion ROI, incrementality, cannibalization analysis, and scenario simulations.
• Partner with Data Science and Analytics teams to translate RGM problems into model requirements, business rules, test cases, success metrics, and decision workflows.
• Support the development of AI-enabled decision tools such as price waterfall cockpits, PPA simulators, promo ROI advisors, bundle simulators, and self-serve insight assistants.
• Leverage GenAI and conversational analytics to accelerate insight generation, executive summaries, market signal synthesis, and adoption of self-serve decision support.
• Design dashboards, scorecards, and decision-first views in tools such as Power BI, Qlik, Tableau, or similar platforms, ensuring insights are simple, actionable, and business-ready.
• Partner with Sales, Marketing, Finance, Category, E-commerce, Analytics, IT, and regional teams to embed RGM recommendations into planning, business reviews, customer discussions, and execution routines.
• Build scalable frameworks, governance, guardrails, playbooks, and learning loops to improve consistency of RGM decisions across markets and channels.
• Champion responsible, human-in-the-loop use of AI, ensuring transparency, explainability, privacy, business accountability, and appropriate challenge of model outputs.

• You have 10+ years of experience across Revenue Growth Management, Pricing, Commercial Strategy, Trade Marketing, Sales Finance, Category Management, Commercial Analytics, Data Science, or related roles.
• You bring strong RGM fundamentals across pricing, price-pack architecture, promotions, trade spend, portfolio mix, gross-to-net / pocket price waterfall, and retailer or customer profitability.
• You have hands-on or close working experience with analytics models in areas such as price elasticity, demand forecasting, promotional uplift, incrementality, optimization, scenario planning, or commercial analytics.
• You are comfortable working with large commercial datasets such as sell‑in, sell‑out / POS, pricing, promotions, trade terms, customer margin, e‑commerce pricing, competitor pricing, and market share data.
• You can translate business problems into data science requirements, define business logic, guide feature selection, review model outputs, challenge assumptions, and convert findings into commercial action.
• You have strong analytical and technical fluency, ideally including advanced Excel, SQL, and exposure to Python or R; experience with Power BI, Qlik,…