Own the Oncology AI product strategy and roadmap across discovery, translational science, clinical development, and real-world evidence.
Lead and manage a cross functional team of AI engineers, providing technical direction, prioritization, and coaching.
Translate complex scientific and operational problems into clear AI product requirements, success metrics, and delivery plans.
Partner with Oncology scientific leaders, clinical teams, Digital, Enterprise AI, and IT to ensure solutions are aligned with enterprise platforms and governance.
Evaluate AI concepts, prototypes, and technical approaches, providing informed guidance and trade‑off decisions.
Assess Oncology workflows to identify and propose opportunities for automation and process improvements.
Drive stakeholder engagement, change management, and adoption, ensuring AI solutions move beyond pilots to sustained impact.
Establish lightweight governance, delivery standards, and value tracking for Oncology AI initiatives.
Represent Oncology AI initiatives in leadership forums and cross-enterprise discussions.

PhD in Computer Science, Machine Learning, Data Science, Software Engineering, AI, or a related discipline and a minimum of 5 years of applied analytical experience with demonstrated impact in operations, automation, business analytics, or decision support OR Master’s in Computer Science, Machine Learning, Data Science, Software Engineering, AI, or a related discipline and a minimum of 7 years of applied analytical experience
Demonstrated impact leading AI enabled products, platforms, or analytics solutions in pharma, biotech, healthcare technology, or AI startups
Strong understanding of Oncology R&D workflows and the role of data and AI in scientific and clinical decision making
Proven ability to lead multidisciplinary technical teams in a matrixed environment
High technical fluency enabling effective evaluation of AI/ML approaches without hands on development
Excellent communication and stakeholder management skills.
Experience operating at the intersection of science, product management, and engineering (preferred)
Familiarity with AI/ML concepts including data pipelines, model development, and prototyping workflows (preferred)
Experience scaling AI solutions in large, regulated organizations (preferred)

401(k) plan with Pfizer Matching Contributions
Additional Pfizer Retirement Savings Contribution
Paid vacation
Holiday and personal days
Paid caregiver/parental and medical leave
Health benefits including medical, prescription drug, dental and vision coverage
Participation in Pfizer’s Global Performance Plan with a bonus target of 20.0% of base salary
Eligibility to participate in share-based long term incentive program

Director, Oncology AI Product – Engineering Lead

Key skills