AI Strategy Lead — Oncology Clinical Development

AstraZeneca; Kendall Square (MA); On-site; USD 144,000 - 216,000; Full time

Benefits offered by this job

Incentives

Equity-based awards

Job summary

AstraZeneca in Kendall Square is seeking a technical lead to advance AI for clinical development across oncology pathways, partnering with biometrics and study teams to design and validate AI-enabled study designs.

The role requires a PhD in a quantitative field and post-PhD experience with measurable impact, plus strong software and biology knowledge to bridge data science and translational research. Competitive compensation and incentives are offered.

Qualifications

• PhD in a quantitative field (e.g., CS, bioinformatics, math, biostatistics).
• At least 2+ years' work experience with measurable impact after PhD.

Responsibilities

• Contribute to the AI strategy and roadmap for Oncology early and late phase clinical development.
• Serve as a key technical lead and contributor in matrixed teams to deliver complex AI projects.
• Evaluate and develop cutting-edge AI methods in problem definition, data considerations, governance, algorithm development, validation, and adoption.
• Partner with clinical development, biometrics, regulatory, and study teams to develop and validate AI solutions into clinical study design and decision-making.
• Establish external collaborations with academia, technology partners, and industry consortia to access novel capabilities.
• Represent AstraZeneca at scientific conferences and contribute publications in ML and clinical AI journals.
• Mentor and support peers within the team.

Skills

ML fundamentals

Coding skills

Biology knowledge

Temporal modeling

Education

PhD in a quantitative discipline

Tools

Frontier coding frameworks

Computing hardware knowledge

Job description

AstraZeneca in Kendall Square is seeking a technical lead to advance AI for clinical development across oncology pathways, partnering with biometrics and study teams to design and validate AI-enabled study designs.

The role requires a PhD in a quantitative field and post-PhD experience with measurable impact, plus strong software and biology knowledge to bridge data science and translational research. Competitive compensation and incentives are offered.