Lead Scientific AI Engineer – Oncology Discovery

Pfizer; Cambridge (MA); On-site; USD 139,000 - 232,000; Full time

Benefits offered by this job

401(k) Matching Contributions

Paid vacation

Holiday and personal days

Paid caregiver/parental leave

Health benefits (medical, prescription

Job summary

Pfizer Oncology is seeking a Scientific AI Engineer to design and build end-to-end AI solutions that shape Oncology R&D decisions. This role blends deep scientific understanding with hands-on AI engineering to translate complex questions into practical AI outputs.

You will partner with Oncology scientists, clinicians, and product leaders to prototype, iterate, and deliver AI-enabled insights with speed, scientific rigor, and real-world usability.

Qualifications

• Bachelor’s degree plus 6+ years or Master’s with 5+ years; PhD with 1+ year in computational biology, data science, ML, or related field.
• Experience building applied AI/ML solutions in life sciences, healthcare, or advanced analytics.
• Strong Python programming and data pipelines / ML frameworks.
• Solid understanding of Oncology biology, translational science, or clinical development workflows.
• Ability to operate independently in ambiguous problem spaces and deliver working prototypes.

Responsibilities

• Design, develop, and prototype AI/ML solutions for oncology discovery and clinical development.
• Apply ML to multimodal datasets (molecular, clinical, real-world, literature).
• Own end-to-end solutions from framing to outputs.
• Collaborate with domain experts to ensure scientific grounding.
• Iterate rapidly on prototypes based on user feedback.
• Contribute technical input to solution design discussions.
• Document methods, assumptions, and limitations for transparency.

Skills

Python

Data pipelines

ML frameworks

Independent work

Education

Bachelor’s degree + 6+ years

Master’s degree + 5+ years

PhD + 1+ years

Tools

Python

Job description

Pfizer Oncology is seeking a Scientific AI Engineer to design and build end-to-end AI solutions that shape Oncology R&D decisions. This role blends deep scientific understanding with hands-on AI engineering to translate complex questions into practical AI outputs.

You will partner with Oncology scientists, clinicians, and product leaders to prototype, iterate, and deliver AI-enabled insights with speed, scientific rigor, and real-world usability.