Data, Analytics & Platform Head

Job Description

Key responsibilities:

Own and evolve a single, trusted view of business‑critical data across Commercial, Medical Affairs, and Value & Access, ensuring data quality, governance, and compliance.

Translate international data, digital, and AI strategy into localized roadmaps and priorities that deliver measurable business and patient impact

Lead the deployment, adoption, and change management of enterprise marketing, medical, and access technology platforms in alignment with global guidance.

Enable advanced analytics, reporting, and dashboards that improve decision quality, execution cadence, and cross‑functional performance.

Drive the local AI and GenAI agenda, scaling use cases that improve customer engagement, productivity, and operational excellence while ensuring responsible AI practices

Partner closely with Integrated Insights and international DAP teams to align KPIs, reporting standards, and technology readiness for global programs (e.g., ICE, IMEx)

Oversee DAP budget, vendor selection, and external partner performance, ensuring delivery against SLAs and strategic objectives

Ensure data and platform readiness to support medical, access, and patient service solutions in accordance with legal, privacy, and compliance requirements.

Build and lead a high‑performing, future‑ready team, fostering innovation, strong adoption, and a culture of accountability and continuous improvement.

Essential Requirements:

Strategic agility: the successful candidate can anticipate future consequences and trends accurately; has broad knowledge and perspective; is future oriented; can clearly articulate a vision and possibilities; can create competitive and breakthrough strategies and plans

Has a high prioritization mindset

Ability to evaluate and import new/untested/innovative models

Experience in working with multiple internal and external stakeholders around a common goal

Proven track record on influencing senior leaders in complex project(s) & driving positive impact

Desirable Requirements:

Enterprise-level data architecture, governance and analytics foundation

Hands-on AI / ML capability from pilot to production