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  1. Home
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  5. Director, Oncology AI Product & Engineering Lead
Pfizer logo

Director, Oncology AI Product & Engineering Lead

Not Disclosed•Full-TimeOn-site

location_on4, East 64th Street, Lenox Hill, Manhattan Community Board 8, Manhattan, New York County, New York, 10065, United States

Apply Now

About the Team

Pfizer Oncology is building an AI-first R&D engine where artificial intelligence is a foundational capability shaping how medicines are discovered, developed, and delivered to patients. Our mission is to transform the scientific landscape by leveraging data and technology to accelerate the creation of life-changing therapies.

About the Role

As the Director, Oncology AI Product & Engineering Lead, you will own the translation of Oncology R&D needs into high-impact AI products and solutions. This role serves as the critical bridge between scientific ambition and technical execution.

You will lead a multidisciplinary team of AI engineers and science-focused technologists, defining the Oncology AI product roadmap while partnering closely with scientific, clinical, digital, and enterprise stakeholders. Your focus will be on identifying opportunities for process automation and simplification, ensuring that solutions are adopted, scalable, and decision-relevant. While this position does not require hands-on coding, it demands strong technical fluency, scientific credibility, and product leadership to evaluate AI concepts, prototypes, and technical approaches effectively.

Hiring Process

Candidates selected for this role will undergo a structured interview process designed to assess technical leadership, strategic vision, and cultural fit. This typically includes an initial screening, followed by deep-dive discussions with leadership and cross-functional partners, and concludes with a final review before an offer is extended.

Equal Opportunity & Culture

Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. We strive to create an inclusive environment where diverse perspectives drive innovation.

Pfizer endeavors to make our careers website accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process and/or interviewing, please email disabilityrecruitment@pfizer.com. This channel is reserved solely for accommodation requests regarding the application and interview process.

Employment Eligibility

Candidates must be authorized to be employed in the U.S. by any employer. U.S. work visa sponsorship (such as TN, O-1, H-1B, etc.) is not available for this role now or in the future. This position requires permanent work authorization in the United States.

Transparency Notice

Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws (the Sunshine Act). If you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address, and the amount of payments made will be reported to the government.

Work location

Work model: On-site

location_on

4, East 64th Street, Lenox Hill, Manhattan Community Board 8, Manhattan, New York County, New York, 10065, United States

New York, New York

Key Responsibilities

  • check_circleOwn the Oncology AI product strategy and roadmap across discovery, translational science, clinical development, and real-world evidence
  • check_circleTranslate complex scientific and operational problems into clear AI product requirements, success metrics, and delivery plans
  • check_circlePartner with Oncology scientific leaders, clinical teams, Digital, Enterprise AI, and IT to ensure solutions are aligned with enterprise platforms and governance
  • check_circleAssess Oncology workflows to identify and propose opportunities for automation and process improvements
  • check_circleDrive stakeholder engagement, change management, and adoption, ensuring AI solutions move beyond pilots to sustained impact
  • check_circleEstablish lightweight governance, delivery standards, and value tracking for Oncology AI initiatives
  • check_circleRepresent Oncology AI initiatives in leadership forums and cross-enterprise discussions

Requirements

  • verifiedPhD in CS, ML, Data Science, Software Engineering, AI, or related field with 5+ years applied analytical experience OR Master's in same fields with 7+ years
  • verifiedDemonstrated impact leading AI-enabled products in pharma, biotech, healthcare tech, or AI startups
  • verifiedStrong understanding of Oncology R&D workflows
  • verifiedPermanent work authorization in the United States
  • verifiedNo U.S. work visa sponsorship available

Nice to Have

Experience operating at the intersection of science, product management, and engineering. Familiarity with AI/ML concepts including data pipelines, model development, and prototyping workflows. Experience scaling AI solutions in large, regulated organizations.

Benefits & Perks

check_circle401(k) plan with Pfizer Matching Contributions and additional Pfizer Retirement Savings Contributioncheck_circlePaid vacation, holiday, and personal dayscheck_circlePaid caregiver, parental, and medical leavecheck_circleHealth benefits including medical, prescription drug, dental, and vision coverageParticipation in Global Performance Plan with 20% bonus target
Pfizer logo
Company

Pfizer

Industry

it

View company profilearrow_forwardlanguageWebsite
Quick Overview

Experience

5+ yrs (Executive)

Education

PhD in CS/ML/Data Science/AI or related field with 5+ years experience

Job Type

Full-Time

Skills Required

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Skills, education and keywords

Skills: Computer Science, Machine Learning, Data Science, Software Engineering, Ai, Pharma, Biotech, Healthcare Technology, Oncology, Data Pipelines.

Education: PhD in CS/ML/Data Science/AI or related field with 5+ years experience; Master's in CS/ML/Data Science/AI or related field with 7+ years experience.

Frequently asked questions about Director, Oncology AI Product & Engineering Lead at Pfizer

What does a Director, Oncology AI Product & Engineering Lead at Pfizer do?expand_more
Day-to-day, the Director, Oncology AI Product & Engineering Lead at Pfizer will own the oncology ai product strategy and roadmap across discovery, translational science, clinical development, and real-world evidence; 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; and assess oncology workflows to identify and propose opportunities for automation and process improvements.
What are the requirements for this Director, Oncology AI Product & Engineering Lead role?expand_more
Pfizer is looking for candidates who meet the following requirements: PhD in CS, ML, Data Science, Software Engineering, AI, or related field with 5+ years applied analytical experience OR Master's in same fields with 7+ years; Demonstrated impact leading AI-enabled products in pharma, biotech, healthcare tech, or AI startups; Strong understanding of Oncology R&D workflows; Permanent work authorization in the United States; and No U.S. work visa sponsorship available.
Where is the Director, Oncology AI Product & Engineering Lead role at Pfizer located?expand_more
Director, Oncology AI Product & Engineering Lead at Pfizer is based in 4, East 64th Street, Lenox Hill, Manhattan Community Board 8, Manhattan, New York County, New York, 10065, United States. This is a on-site role.
Is this Director, Oncology AI Product & Engineering Lead job remote, hybrid, or on-site?expand_more
Pfizer has listed this Director, Oncology AI Product & Engineering Lead role as on-site.
How much experience is required for this Director, Oncology AI Product & Engineering Lead role?expand_more
Director, Oncology AI Product & Engineering Lead at Pfizer typically requires 5+ years of relevant experience at the executive level.
What skills do you need for the Director, Oncology AI Product & Engineering Lead role at Pfizer?expand_more
Key skills for Director, Oncology AI Product & Engineering Lead at Pfizer include Computer Science; Machine Learning; Data Science; Software Engineering; Ai; Pharma; Biotech; and Healthcare Technology.
What education is required for Director, Oncology AI Product & Engineering Lead at Pfizer?expand_more
Educational requirements for this role: PhD in CS/ML/Data Science/AI or related field with 5+ years experience; and Master's in CS/ML/Data Science/AI or related field with 7+ years experience.
What category does the Director, Oncology AI Product & Engineering Lead role belong to?expand_more
Director, Oncology AI Product & Engineering Lead at Pfizer is part of the it job category on Recrutus.
Recrutus

Curating the world's most innovative career opportunities. We bridge the gap between visionary talent and industry-leading companies.

Search roles by city, category, skill, or job type — explore verified US employers, salary benchmarks, and remote-friendly teams hiring nationwide.

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About usFAQContactPrivacy policy

Recrutus helps candidates discover roles that match their skills and helps teams reach qualified applicants faster. Browse by metro, discipline, or work style — from internships to senior leadership.

© 2026 Recrutus. All rights reserved.
Terms of serviceCookie policyAcceptable useDMCA policyEmployer termsCandidate terms
check_circle
Evaluate AI concepts, prototypes, and technical approaches, providing informed guidance and trade-off decisions
  • check_circleLead and manage a cross-functional team of AI engineers, providing technical direction, prioritization, and coaching
  • check_circle
    check_circleEligibility for share-based long-term incentive program
    check_circleRelocation assistance available based on business needs and eligibility
    Computer ScienceMachine LearningData ScienceSoftware EngineeringAiPharmaBiotechHealthcare TechnologyOncologyData Pipelines
    US privacy notice
    Accessibility