Senior Director, R&D FIT Domain Lead (Secondment - 12 Months)

WHY PATIENTS NEED YOU

You will own the end‑to‑end digital and AI portfolio for Pfizer's Business Innovation team; in this role you will serve as a primary Digital & Technology partner to the domain’s senior leadership team. This role reports to the Vice President, R&D Forward Impact Engineering & Engagement Team within Pfizer’s Digital and Technology division.

WHAT YOU WILL ACHIEVE

Operating at two critical altitudes, you will:

Strategic Thinking & Innovation

Shape a bold, multi‑year digital and AI vision; align investments to enterprise priorities and Bold Moves; and introduce new digitally enabled business models that transform R&D operations and outcomes.

Speed‑to‑Value through MVP‑First Experimentation

Drive rapid prototyping and iterative delivery to validate hypotheses quickly, capture insights, and scale successful solutions into resilient, compliant, and cost‑effective enterprise capabilities.

You will also lead the cultural change to product thinking—moving the organization from project delivery to a user‑centric, value‑driven product model—and run portfolio governance, demand management, and budget planning across your domain.

HOW YOU WILL ACHIEVE IT

Strategic Thinking & Innovation (Altitude #1)

• Develop and communicate a multi‑year vision and strategy for the R&D digital and AI portfolio, aligned to enterprise priorities and measurable business outcomes.

• Establish portfolio governance with clear OKRs, outcome targets, and ROI/TCO measures; manage P&L across the product suite.

• Continuously scan market, technology, and regulatory trends to surface high‑impact opportunities (AI/ML, data platforms, workflow automation) and inform roadmaps.

• Shape digitally enabled business models and operating mechanisms that reduce cycle time, increase quality, and improve risk posture across R&D.

Speed‑to‑Value via MVP‑First (Altitude #2)

• Lead a rapid prototyping / MVP‑first approach with disciplined guardrails (hypotheses, success criteria, risk & compliance checks) to accelerate time‑to‑value.

• Ensure MVPs are user‑centric, data‑driven, and extensible; guide the transition of validated MVPs to production‑grade products (performance, reliability, security, observability, scalability).

• Apply dual‑track agile (discovery + delivery) with short cycles, fast feedback loops, and continuous improvement.

Product Thinking Cultural Change

• Act as a change agent—embed product thinking and shift from project execution to value‑driven, user‑centric product operating rhythms (e.g., DSU, BLP, QBR).

• Coach leaders and teams on hypothesis‑driven discovery, prioritization by value, iterative delivery, and product telemetry.

• Create playbooks, forums, and storytelling practices that normalize experimentation, measurable outcomes, and learning.

Portfolio Governance, Demand & Budget Management

• Lead demand intake and prioritization across R&D in partnership with stakeholders; ensure transparent communication of priorities and trade‑offs.

• Prepare and manage the annual Digital budget for the R&D portfolio with input from Architecture, Engineering, Data/AI, Security/Compliance, and Product Operations.

• Balance investments across experiments, MVPs, scale‑ups, core products, and platforms, optimizing for ROI, risk, and lifecycle health.

Lifecycle, Platforms & Scaled Delivery

• Build and maintain R&D roadmaps and release plans; report quarterly on outcomes, adoption, financials, and risk.

• Connect horizontal platforms (identity, workflow, data/analytics, AI foundation models, MLOps) to deliver a holistic end‑user experience and reduce duplicate spend.

• Champion agile/lean at scale, reusability, observability, DevSecOps/SRE, and support models aligned to product criticality.

AI, Data & Compliance Leadership

• Implement responsible AI (bias testing, explainability, human‑in‑the‑loop, model monitoring) and ensure adherence to GxP, privacy, security, and model risk management.

• Promote data product practices (FAIR principles, lineage, data quality SLAs, feature stores) that underpin reliable AI/ML outcomes.

• Partner with Architecture, Security, and Compliance to maintain audit readiness and alignment to enterprise architecture patterns.

Stakeholder Engagement & Communication

• Build trusted relationships across R&D; co‑create strategies and operating mechanisms; ensure transparent trade‑off