Principal Product Manager, Customer-Deployed

Overview

In this role you will spearhead ICIS’s first forward-deployed product team, collaborating directly with chemicals customers to define discovery-led development. You’ll identify high-value problems, validate quickly, and demonstrate measurable commercial value through pilots and scalable patterns. You will lead cross-functional squads, own customer relationships, and shape product direction from discovery to shipped outcomes. This is a high-impact opportunity to influence product strategy and customer value in a fast-moving, data-driven environment.

Pay / Benefits

• country specific benefits

Responsibilities

• Lead 2–3 active forward-deployed initiatives with named chemicals customers
• Deliver the first working PoC to a customer within 60 days
• Drive the first paid pilot to go live within one quarter
• Own the squad’s discovery and delivery rhythm with weekly customer engagement
• Maintain a live discovery view for every initiative
• Act as the taste gate to ensure PoC before PRD creation
• Make kill/pivot/promote decisions based on evidence and customer value
• Create playbooks and enablement materials for Sales and central teams when patterns are validated

Key requirements

• Track record in customer-back, forward-deployed or embedded product work
• Shipped intelligence, workflow or platform outcomes into complex customer organisations with measurable impact
• Experience in strategy or transformation consulting with ownership of a shipped customer outcome
• Customer judgement at senior levels
• Leadership through influence in cross-functional settings
• Commercial judgement translating customer reality into product direction and prioritisation
• Technical fluency to engage with engineering and data science teams; familiarity with AI production patterns (RAG, evals, agents, tool use, MCP)
• Comfort working in ambiguity and delivering measurable outcomes
• Strong communication tailored to customers, technical stakeholders, and senior leadership
• Alignment with Data Services Mindset and RELX Leadership Excellence; adherence to Responsible AI Principles

• leadership through influence
• customer-centric communication
• ambition and adaptability
• AI production patterns (RAG, evals, agents, tool use, MCP)
• engaging with engineering and data science teams
• modern product delivery in AI-enabled environments

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