Associate Director, Clinical AI

Posted date Sep. 21, 2026
Contract type Full time
Job ID R\-260355

Why choose AstraZeneca Spain?
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AstraZeneca Spain is a rising force in our global business. With headquarters in Madrid and our global hub in Barcelona, we’ve become an important international centre of excellence in the fight against critical disease. Boasting vibrant universities and business schools, the Barcelona ecosystem is a place where scientists can thrive. We attract a diverse workforce from across the globe, shining a beacon for innovation in a country that’s committed to clinical development.

We invite you to bring your talents to Barcelona where our respiratory medicine R\&D and Global Marketing centre offers opportunities in R\&D, IT, Commercial and HR. Or join us in Madrid and shape our growth in our BUs (Respiratory, Oncology \& CVRM ), and a range of Corporate functions. Additionally, you can find sales roles throughout the country. Together, we’re contributing to a world\-leading pipeline of therapeutics and delivering life\-changing medicines to patients.

Who do we look for?
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Calling all tech innovators, ownership takers, challenge seekers and proactive collaborators. At AstraZeneca Spain, breakthroughs born in the lab become transformative medicine for the world's most complex diseases. Alongside technical expertise, colleagues have the resilience, energy and collaborative mindset to change lanes, work with different teams and start projects from scratch.

Here, diverse minds and bold disruptors can meaningfully impact the future of healthcare using cutting\-edge technology. Whether you join us in Madrid or Barcelona, you can make a tangible impact within a global biopharmaceutical company that invests in your future. Join a talented global team that's powering AstraZeneca to better serve patients every day.

Success Profile
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Ready to make an impact in your career? If you're passionate, growth\-orientated and a true team player, we'll help you succeed. Here are some of the skills and capabilities we look for.

Diverse collaborators

This is a speak\-up culture that values collaboration. You’ll proactively bring your unique perspectives, experiences and skills to the table and seek the same from others. With our international team composition and the need for fast\-paced collaboration, you’ll always be building new connections with colleagues.

Cutting\-edge innovators

When you join us, you’ll be part of a team that embraces digital technology and data to transform the way we work and the work we do. Every day, you’ll help make history, empowered to ignite your creativity and build something enduring.

Resilient trailblazers

Here, the answers aren’t always available. So, you’ll need to bring a fearless, self\-starter mindset to navigate uncharted territories. You’ll harness your ceaseless energy to discover and make the necessary connections with colleagues to shape the future and achieve maximum impact.

Agile movers

Seize ownership and excel with autonomy to enjoy the constant rush of ground\-breaking discovery. Your ability to anticipate sudden shifts and adapt swiftly will prove critical as you make your mark in an environment that rewards initiative and resilience.

Responsibilities
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Job ID R\-260355 Date posted 09/21/2026
About AstraZeneca and AISI

At AstraZeneca, technology and science meet to change what is possible for patients. We are building a connected, end\-to\-end Enterprise AI engine — uniting data foundations, AI technology, process reinvention, and business\-facing AI to accelerate results across the whole value chain. Success depends on being exceptional connectors: you will actively leverage existing capabilities, celebrate and promote reuse, export breakthrough ideas across geographies and functions, and obsess over scaling impact rather than building in isolation.

AI Science \& Innovation (AISI) sits at the centre of AstraZeneca's R\&D AI transformation. Our remit is to build, buy, and deliver the AI models and agents that change pipeline outcomes, across discovery, translational science, biomarkers, and clinical development.

Within AISI, the BioPharma Clinical Development AI team is building world\-class AI capability to accelerate the design, conduct, and analysis of clinical trials across our BioPharmaceuticals pipeline — spanning both early and late phase programmes. We partner closely with clinical development, regulatory, and biometrics teams to bring better treatments to patients faster, while adhering to the highest evidentiary standards.

The Opportunity

Bringing new treatments to patients demands scientific excellence at every stage of development. In the AI for Clinical Development, BioPharma AIR\&D team, we focus on one of the most data\-rich and decision\-intensive parts of that journey: clinical development. Trial design, patient selection, dose optimisation, biomarker strategy, and safety evaluation each represent genuine opportunities where AI and machine learning can add rigour, speed, and precision — not as a replacement for clinical and statistical expertise, but as a powerful complement to it. We hold ourselves to measurable standards of improvement, and we build methods that can be evaluated, reproduced, and trusted in regulatory settings.

You will work across the enterprise to define and deliver on AstraZeneca's most pressing clinical development questions — collaborating in cross\-functional teams spanning the key BioPharmaceuticals disease areas of cardiovascular, renal, metabolic disease, respiratory, and immunology. You and the team will apply new methods to measurably advance the late\-stage drug pipeline, and you will help invent reusable approaches that scale across programmes and geographies.

AI for clinical development is a field in motion. Foundation models, agentic systems, and causal AI are advancing rapidly, and the regulatory and methodological frameworks around them are evolving in parallel. As an Associate Director, Data Scientist in the AI for Clinical Development team, you will be hands\-on at the frontier — developing, evaluating, and deploying AI methods that directly inform clinical trial design and decision\-making across early and late phase programmes. Every model you build will eventually touch a trial that decides whether a patient gets a better therapy. That is the bar we hold ourselves to.

Key Responsibilities

• Develop, evaluate, and deploy reusable AI and machine learning methods for clinical trial settings — including innovative trial design support, dose optimisation, biomarker discovery, digital twins and predictive modelling for early and late phase decisions, and safety and efficacy signal detection.


• Lead end\-to\-end delivery of data science projects, from problem framing and methodology selection through to implementation, validation, and adoption within study teams.


• Partner with Clinical Development, Study Teams, Biometrics, and Regulatory colleagues to embed AI and analytical strategy into study design and decision\-making workflows.


• Build reusable, well\-documented data products — including pipelines, packages, and applications — with a software engineering mindset, ensuring quality, reproducibility, and maintainability across the enterprise.


• Apply and evaluate cutting\-edge methodologies, including foundation models, agentic AI systems, generative patient models, longitudinal and time\-series modelling, Bayesian inference, and causal inference, proposing fit\-for\-purpose approaches with clear evaluation criteria.


• Drive data\-centric AI practices: acquire, curate, and quality\-control datasets for model training, post\-training, benchmarking, and evaluation in clinical and regulatory settings.


• Contribute to the development of AI evaluation and benchmarking frameworks suitable for clinical and regulatory settings.


• Engage actively with internal data science communities and external scientific forums; contribute to publications and conference presentations as a recognised scientific contributor.


• Provide coaching and technical guidance to Senior Data Scientists and peer colleagues, promoting best practice and a culture of scientific rigour.

• PhD preferred; MSc with an exceptional computational track record considered. Disciplines: Computer Science, Machine Learning, Statistics, Mathematics, Biomedical Informatics, Computational Biology, or a closely related quantitative field.


• 2–5 years of post\-PhD (or equivalent) experience in AI and machine learning method development, with demonstrated impact in clinical, biomedical, or drug development settings (e.g. models delivered, first\-author publications, open\-source contributions, SaMD filings).


• 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 technical expertise in modern AI methodologies, including one or more of: 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.


• Exceptional software development skills in Python, leveraging frontier coding agent frameworks; experience with deep learning frameworks (e.g. PyTorch) and modern LLM tooling.


• Demonstrated experience building and deploying robust, reusable analytical solutions, including familiarity with cloud platforms (e.g. AWS, Azure, GCP).


• Proven track record of translating complex methodologies into actionable insights and embedding solutions within cross\-functional teams.


• Excellent written and

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