Strategic AI Leader — Clinical Development

AstraZeneca GmbH; Barcelona; Híbrido; EUR 120.000 - 180.000; Jornada completa

Descripción de la vacante

AstraZeneca seeks a Director, Data Scientist to shape the AI methodology for Clinical AI programmes across early and late-stage development in Cardiovascular, Renal, Metabolic, Respiratory, Immunology and cell-therapy areas. You will define and drive strategies, influence across functions, and advance enterprise AI methods with external collaborations.

You will lead high-impact AI projects, ensure regulatory-aligned evidence, and promote data-centric practices while mentoring teams and

Formación

• PhD in Computer Science, Machine Learning, Statistics, Mathematics, Biomedical Informatics, Computational Biology, or a closely related quantitative discipline — with a strong, hands-on computational track record.
• 4–8 years of post-PhD experience in AI and machine learning method development, with demonstrated and sustained impact in clinical, biomedical, or drug development settings (e.g. models delivered, first-author publications, patents, SaMD filings, open-source projects).
• Deep experience, knowledge, and understanding of one or more fields of biology, with hands-on experience working with biological data such as molecular (DNA, RNA, protein), imaging (radiology, microscopy), or clinical text (EHR, clinical notes).
• Deep expertise in modern AI methodologies, including foundation model training and fine-tuning; Bayesian inference; temporal and longitudinal modelling; multimodal integration; model calibration and domain adaptation; data-centric AI; model interpretability; model post-training and alignment.
• Excellent software engineering skills: Python, deep learning frameworks (e.g.PyTorch), frontier coding agent frameworks, modern LLM tooling, and cloud platforms (AWS, Azure, GCP).
• Demonstrated experience translating AI methods into applications that inform clinical and/or biomedical decisions, including prospective evaluation or contribution to submission-relevant evidence.
• Track record of driving scientific influence across cross-functional communities — ML, clinical, biostatistics, regulatory — without relying on formal authority.
• Peer-reviewed publications in clinical AI, computational drug development, or leading ML venues (e.g.NeurIPS, ICML, ICLR, Nature Medicine, Lancet Digital Health).
• Excellent written and verbal communication skills, with demonstrated ability to translate technical findings for clinical, regulatory, and executive audiences.

Responsabilidades

• Define and drive the AI methodology roadmap for assigned Clinical AI programmes, spanning early and late phase clinical development, and aligning AI/ML priorities with clinical and business objectives.
• Lead, by matrix influence and scientific authority, the delivery of the most complex and high-stakes AI projects — from problem definition and methodology selection through validation, regulatory alignment, and scaled adoption across the enterprise.
• Develop and govern reusable, enterprise-grade AI methods and evaluation frameworks for clinical trial settings, including innovative trial design support, dose optimisation, biomarker discovery, digital twins, predictive and prognostic modelling, and safety and efficacy signal detection.
• Champion data-centric AI practices at programme level: govern the acquisition, curation, and quality control of datasets for model training, post-training, benchmarking, and evaluation across clinical and regulatory settings.
• Partner with Clinical Development, Biometrics, Regulatory, and Study Teams to embed AI strategy and validated solutions into study design and decision-making at programme level.
• Shape the AI evidence component for regulatory submission packages; act as the scientific and methodological voice in regulatory engagements involving AI/ML methods or innovative trial designs (FDA, EMA, MHRA).
• Evaluate and champion cutting-edge AI methodologies — including foundation models, agentic AI systems, generative patient models, multimodal learning, Bayesian inference, causal inference, and model calibration and domain adaptation — proposing fit-for-purpose approaches with robust evaluation criteria and risk assessment.
• Establish and maintain external collaborations with academic institutions, technology partners, and industry consortia to access novel capabilities and advance the scientific agenda.
• Represent AstraZeneca at scientific conferences, standards bodies, and peer-reviewed venues; contribute first- or last-author publications in leading ML and clinical AI journals.
• Serve as a technical mentor and thought partner for Associate Directors and Senior Data Scientists within the Clinical AI team; promote scientific rigour, reuse, and a culture of learning in public.
• Contribute to the broader AISI AI for Clinical Development strategy, including cross-functional ways of working, tooling governance, and methodology standards.

Conocimientos

Communication skills

Written communication

Leadership

Educación

PhD in computer science, ML, statistics, mathematics, bioinformatics, computational biology

Herramientas

Python

PyTorch

LLM tooling

Agent frameworks

AWS

Azure

GCP

Descripción del empleo

AstraZeneca seeks a Director, Data Scientist to shape the AI methodology for Clinical AI programmes across early and late-stage development in Cardiovascular, Renal, Metabolic, Respiratory, Immunology and cell-therapy areas. You will define and drive strategies, influence across functions, and advance enterprise AI methods with external collaborations.

You will lead high-impact AI projects, ensure regulatory-aligned evidence, and promote data-centric practices while mentoring teams and