Director, Oncology AI Product & Engineering Lead
Pfizer
August 11, 2026
Remote friendly (New York, NY)
United States
IT
Key Responsibilities
- 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; provide technical direction, prioritization, and coaching.
- Translate complex scientific and operational problems into AI product requirements, success metrics, and delivery plans.
- Partner with Oncology scientific leaders, clinical teams, Digital, Enterprise AI, and IT to align solutions with enterprise platforms and governance.
- Evaluate AI concepts, prototypes, and technical approaches; guide trade-offs.
- Assess Oncology workflows to identify opportunities for automation and process improvements.
- Drive stakeholder engagement, change management, and adoption beyond pilots to sustained impact.
- Establish lightweight governance, delivery standards, and value tracking.
- Represent Oncology AI initiatives in leadership forums and cross-enterprise discussions.
Basic Qualifications
- PhD (or Master’s) in Computer Science/ML/Data Science/Software Engineering/AI or related field with 5+ (or 7+) years applied analytical experience in operations, automation, business analytics, or decision support.
- Demonstrated impact leading AI-enabled products/platforms/analytics in pharma, biotech, healthcare tech, or AI startups.
- Strong understanding of Oncology R&D workflows and the role of data/AI in scientific/clinical decision making.
- Proven ability to lead multidisciplinary technical teams in a matrixed environment.
- High technical fluency to evaluate AI/ML approaches without hands-on development.
- Excellent communication and stakeholder management.
Preferred Qualifications
- Experience at the intersection of science, product management, and engineering.
- Familiarity with AI/ML concepts (data pipelines, model development, prototyping).
- Experience scaling AI solutions in large, regulated organizations.
- 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; provide technical direction, prioritization, and coaching.
- Translate complex scientific and operational problems into AI product requirements, success metrics, and delivery plans.
- Partner with Oncology scientific leaders, clinical teams, Digital, Enterprise AI, and IT to align solutions with enterprise platforms and governance.
- Evaluate AI concepts, prototypes, and technical approaches; guide trade-offs.
- Assess Oncology workflows to identify opportunities for automation and process improvements.
- Drive stakeholder engagement, change management, and adoption beyond pilots to sustained impact.
- Establish lightweight governance, delivery standards, and value tracking.
- Represent Oncology AI initiatives in leadership forums and cross-enterprise discussions.
Basic Qualifications
- PhD (or Master’s) in Computer Science/ML/Data Science/Software Engineering/AI or related field with 5+ (or 7+) years applied analytical experience in operations, automation, business analytics, or decision support.
- Demonstrated impact leading AI-enabled products/platforms/analytics in pharma, biotech, healthcare tech, or AI startups.
- Strong understanding of Oncology R&D workflows and the role of data/AI in scientific/clinical decision making.
- Proven ability to lead multidisciplinary technical teams in a matrixed environment.
- High technical fluency to evaluate AI/ML approaches without hands-on development.
- Excellent communication and stakeholder management.
Preferred Qualifications
- Experience at the intersection of science, product management, and engineering.
- Familiarity with AI/ML concepts (data pipelines, model development, prototyping).
- Experience scaling AI solutions in large, regulated organizations.