Solution Specialist, AI & Data Services (Pharma)

Overview

In this role you drive the commercial and technical evolution of Direct Data Solutions for pharma, acting as the technical lead in client engagements and delivering demonstrations that show how AI-enabled pharma data can be consumed in client environments. You collaborate across teams to shape data strategy, pilots, and production integrations, balancing business value with technical feasibility. Your work helps clients understand data coverage and provenance while contributing to AI-driven offerings and roadmap decisions.

Pay / Benefits

• health benefits
• financial benefits
• fitness programs
• travel benefits
• tech perks
• career development opportunities

Responsibilities

• Serve as the technical lead in client meetings, conducting discovery and translating needs into API, MCP, Snowflake, and CRM solutions
• Pilot MCP implementations through production, delivering integration guidance and documentation
• Provide clear, honest answers about data coverage, sources, derivation, and refresh cycles
• Collaborate with Research & Analytics and Product to ensure pharma datasets are well-structured and API-friendly
• Assess how AI agents consume our data and identify improvements to the data delivery model
• Contribute to AI-focused commercial offerings, pricing, and proposals; represent GlobalData at clients and events
• Create reusable assets from real client work, including demo patterns, MCP configurations, and documentation

Key requirements

• Experience selling information products and handling client scrutiny of coverage, sourcing, and methodology
• Understanding of pharma workflows (competitive intelligence, clinical operations, medical affairs or commercial analytics) gained in industry, CRO, or CDMO selling into those teams
• Pre-sales, solutions engineering, or technical consulting with direct client ownership
• Ability to build working demonstrations with engineering/AI support, not necessarily a software engineer
• Judgement to scope demos appropriately and the confidence to admit gaps when needed
• Commercial acumen to translate technical solutions into measurable business value
• Comfort working across data engineering discussions and strategic executive-level conversations
• Curious, self-directed, and willing to learn the domain deeply
• Client-facing communication
• Cross-functional collaboration
• Curiosity and self-direction
• MCP
• LangChain
• Claude

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