Experteer Overview

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In this role you will define and drive the AI methodology roadmap for Clinical AI programs across early and late phase development. You will lead high-stakes AI projects with scientific authority, shaping enterprise-grade methods and regulatory-aligned solutions. You’ll partner across Clinical Development, Biometrics, Regulatory, and Study Teams to embed AI strategy into study design.

This is a high-visibility opportunity to influence how AI is used in bio-pharma clinical development and regulatory engagement.

Compensaciones / Incentivos

- Define and drive the AI methodology roadmap for assigned Clinical AI programmes, aligning priorities with clinical and business objectives
- Lead complex AI projects through problem definition, methodology selection, validation, regulatory alignment, and enterprise adoption
- Develop and govern reusable enterprise-grade AI methods for clinical trials (design support, dose optimization, biomarker discovery, digital twins, predictive modelling, safety/efficacy signals)
- Champion data-centric AI practices at programme level: data acquisition, curation, quality control for training and evaluation
- Partner with Clinical Development, Biometrics, Regulatory, and Study Teams to embed AI solutions into study design and decision-making
- Shape the AI evidence component for regulatory submissions; act as scientific voice in AI regulatory engagements (FDA, EMA, MHRA)




- Evaluate and champion cutting-edge AI methodologies (foundation models, agentic AI, causal inference, multimodal learning, model calibration, domain adaptation) with robust evaluation and risk assessment
- Establish external collaborations with academia, technology partners, and industry consortia to advance scientific agenda
- Represent AstraZeneca at scientific conferences and publications; mentor junior scientists to promote rigor and reuse
- Contribute to broader AISI AI for Clinical Development strategy including governance and standards

Responsabilidades

- PhD in a quantitative discipline with hands-on computational track record
- 4–8 years post-PhD in AI/ML method development with impact in clinical/biomedical settings
- Deep experience with biology and biological data (molecular, xugodme imaging, or clinical text)
- Expertise in modern AI methods (foundation models, Bayesian inference, temporal modelling, multimodal integration, domain adaptation, interpretability)
- Exceptional software engineering skills (Python, PyTorch, frontier agent frameworks, LLM tooling, cloud platforms)
- Experience translating AI methods into clinical/biomedical decision support with prospective evaluation or regulatory evidence
- Track record of scientific influence across ML, clinical, biostatistics, regulatory groups without formal authority
- Peer-reviewed publications in clinical AI or ML venues
- Excellent written and verbal communication for clinical, regulatory, and executive audiences

Requisitos principales

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📌 Director, Data Scientist - Clinical AI (Barcelona)
🏢 AstraZeneca
📍 Barcelona