# Director, AI Research at AstraZeneca

AstraZeneca is hiring a Director, AI Research in Boston, United States. It pays $203k-$305k a year and Level rates it Builds AI ●●●●; you can [apply on Level](https://jobsbylevel.com/go/f063f5ac-885a-4b6c-96ca-17e01f5c3d2d?utm_medium=ai-agent).

AI Level 4, AI centrality 97 out of 100. US - Boston - MA.

## Details

- Company: [AstraZeneca](https://jobsbylevel.com/companies/astrazeneca)
- AI level: AI Level 4 (score 97 out of 100)
- Location: US - Boston - MA
- Salary: $203k-$305k
- Posted: October 14, 2026
- Apply: https://jobsbylevel.com/go/f063f5ac-885a-4b6c-96ca-17e01f5c3d2d?utm_medium=ai-agent

## Prepare for this job

The job page lists 5 likely interview questions for this offer, with a CV checklist: https://jobsbylevel.com/jobs/director-ai-research-at-astrazeneca-ecef51

## Description

Job Title: Director, AI Research Introduction to role : Are you ready to bring frontier AI into the heart of clinical development and change how trials are designed, conducted, and analyzed? Can you move seamlessly from a clinical question to the AI system that answers it and stands up to scientific and regulatory scrutiny? In this director-level role, you will define and deliver the AI research agenda that improves decisions for trials and patients across Oncology and BioPharmaceuticals. You will work at the intersection of advanced AI, clinical trial methodology, and biomedical science—translating methodological innovation into capabilities that shape clinical-development strategy and outcomes. You will lead research spanning foundation models, multimodal learning, agentic systems, post-training methods, and evaluation science. Your work may address treatment-effect heterogeneity, predictive biomarker discovery and validation, patient stratification, time-to-event outcomes, cross-trial generalization, and the responsible evaluation and governance of AI systems used in developing new medicines. Accountabilities : Research Strategy and Roadmap: Set and execute a research strategy focused on the highest-impact clinical-development challenges, prioritizing efforts that drive measurable benefits for patients and the pipeline. Method Development for Trials: Invent and refine AI and statistical learning methods tailored to randomized clinical trials and related evidence, with emphasis on heterogeneous treatment effects, predictive biomarkers, time-to-event outcomes, patient stratification, and cross-trial generalization. Agentic AI Systems: Design, build, and rigorously evaluate agentic AI systems for clinical-development use cases, incorporating retrieval, tool use, code execution, memory, multi-step workflows, and human oversight to ensure reliability and reproducibility. Reproducible Engineering: Write high-quality Python and build reproducible research workflows using modern ML frameworks, version control, testing practices, and cloud or high-performance computing environments to accelerate trustworthy science at scale. Scientific Leadership and Influence: Serve as a senior scientific and technical partner, shaping clinical strategy, evaluation approaches, platform capabilities, and investment decisions across the organization. External Dissemination and Partnerships: Share research through peer-reviewed publications, reusable tools, patents, scientific collaborations, and conference presentations; represent the company with partners, consortia, regulators, and the broader research community. Team Culture and Mentorship: Cultivate a rigorous research culture through structured scientific review, constructive challenge, and mentorship of scientists and engineers, raising the bar for impact and integrity. Responsible AI and Governance: Establish robust evaluation, governance, and responsible-use frameworks for advanced AI systems in clinical development, aligning innovation with patient safety and regulatory expectations. Essential Skills/Experience : Hold a PhD in Computer Science, Machine Learning, Biostatistics, Biomedical Informatics, Computational Biology, or a closely related quantitative field, or have an MSc with an equivalent record of research and industry impact. Eight years of experience in original research and technical impact, demonstrated through influential publications, clinical evidence, deployed systems, patents, widely used software or datasets, or comparable contributions. Have led substantial research programs end to end and made scientific or technical decisions that shaped a broader portfolio, platform, or organizational direction. Are comfortable setting direction under uncertainty, challenging assumptions, and influencing senior partners in our organization Bring expertise in relevant research topics, such as unsupervised learning, dimensionality reduction, causal inference, survival or longitudinal

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