Senior AI & Data Engineering Lead – Oncology R&D

Pfizer; Bothell (WA); On-site; USD 139,000 - 232,000; Full time

Job summary

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. We are seeking AI & Data Engineers to focus on generalist, use case driven AI solutions where process, workflow, and data engineering are as critical as advanced science.

This role partners with scientific, clinical, and operational teams to develop data pipelines, analytics, and ML solutions that enhance

Qualifications

• Bachelor’s degree with 6+ years of relevant work experience or advanced degree.
• Hands-on experience building data, analytics, or ML solutions in healthcare.

Responsibilities

• Build and prototype AI enabled solutions supporting Oncology R&D workflows and decision making.
• Develop and maintain data pipelines, feature engineering workflows, and analytical models.
• Apply machine learning techniques to structured and unstructured healthcare data.
• Collaborate with scientific and product partners to understand needs and deliver usable tools.
• Focus on speed, iteration, and usability, with production scaling supported by enterprise Digital teams as appropriate.
• Contribute to shared engineering standards, documentation, and best practices.

Skills

Data engineering

Machine learning

Python

Healthcare data

Education

Bachelor’s degree in computer science, machine learning, or related field

Master’s degree in a quantitative field

PhD with 1+ years of experience in relevant field

Tools

Cloud platforms

ML tooling

Job description

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. We are seeking AI & Data Engineers to focus on generalist, use case driven AI solutions where process, workflow, and data engineering are as critical as advanced science.

This role partners with scientific, clinical, and operational teams to develop data pipelines, analytics, and ML solutions that enhance