Director, Oncology AI Platforms & Commercial Data

AstraZeneca; Gaithersburg (MD); On-site; USD 186,000 - 279,000; Full time

Job summary

AstraZeneca is seeking a strategic AI product owner to drive the lifecycle of GenAI capabilities powering Sales, Marketing, and Medical Affairs across tumor-area portfolios. You will partner across US Oncology and Enterprise AI, turning complex problems into scalable, reusable solutions.

Lead the definition of requirements for LLM-powered apps, manage a prioritized backlog, and ensure pilots translate into measurable field impact, with governance and change management woven into every release.

Qualifications

• End-to-end AI/product ownership with measurable commercial impact in oncology or specialty contexts.
• Bridge brand strategy, commercial ops, data science and technology teams.
• Hands-on with LLMs, prompt engineering, retrieval-augmented generation, agentic AI.
• Experience with oncology commercial data sources (IQVIA, Symphony, MMIT, Komodo, PULSE).
• Excellent communication; thrives in matrixed organizations.

Responsibilities

• Own AI product strategy for Sales, Marketing and Medical Affairs across tumor-area portfolio.
• Lead GenAI/agentic AI product development for field tools and MSLs.
• Define requirements for LLM-powered apps; translate to scalable production solutions.
• Maintain backlog with user stories, acceptance criteria, and timelines.
• Pilot, measure adoption, and scale successful AI capabilities.

Skills

Analytical fluency

Cross-functional collaboration

Strategic product ownership

Prompt engineering

LLMs / GenAI exposure

Communication skills

Education

Bachelor's degree in quantitative field

MBA / MS / PhD (valued)

Tools

Python

Cloud platforms (AWS SageMaker, Databricks, Azure, GCP)

Job description

AstraZeneca is seeking a strategic AI product owner to drive the lifecycle of GenAI capabilities powering Sales, Marketing, and Medical Affairs across tumor-area portfolios. You will partner across US Oncology and Enterprise AI, turning complex problems into scalable, reusable solutions.

Lead the definition of requirements for LLM-powered apps, manage a prioritized backlog, and ensure pilots translate into measurable field impact, with governance and change management woven into every release.