Introduction to role

Are you passionate about turning data into insights that improve patients' lives? Join Late CVRM Biometrics at AstraZeneca and help deliver the next wave of breakthrough medicines for millions of patients. We are opening a position within Late CVRM Biometrics for a Data Science Associate Director, based in Barcelona, Spain. In this role, data, analytics and AI become the engine that accelerates late-stage drug development, working at the intersection of cutting-edge science and modern digital technology. Ready to experiment with new approaches, challenge assumptions and see your work directly influence clinical decisions?

Accountabilities

As a Data Science Associate Director, you will drive the design and delivery of innovative analytics solutions, machine learning models and advanced AI agent technologies that support data-driven decision making and optimize drug development processes. Operating with significant autonomy and strategic influence, this role shapes the Biometrics data science agenda and helps define how data is used across late-stage CVRM programs.

You will shape and deliver strategic data science initiatives across Late CVRM Biometrics and the broader CVRM Therapeutic Area, ensuring alignment with scientific and business priorities.

You will lead end-to-end delivery of analytics, AI/ML and visualization solutions-from problem framing and stakeholder alignment through to implementation, change management and sustained adoption in clinical teams.

A key part of the role is to build reusable data products such as packages, pipelines and applications, with robust documentation, validation and maintainability so that solutions scale across studies and programs.

Collaboration is central: you will establish effective partnerships across internal data science groups, engineering teams and external vendors or academic collaborators to accelerate delivery and amplify impact. You will actively scan the horizon for relevant methods and technologies-such as agentic AI, synthetic data approaches and modern data tooling-proposing fit-for-purpose solutions with clear evaluation criteria, benefits and risk considerations.

You will represent Data Science internally and externally through seminars, communities of practice and scientific forums, helping to grow a culture of experimentation, learning and knowledge sharing. Along the way, you will mentor others, influence senior stakeholders and help embed data science into everyday decision making across Late CVRM.

Essential Skills/Experience

• MSc Degree in Mathematics, Computer Science, Engineering, Physics, Statistics, or a related quantitative field

• Significant in-depth experience in analyzing and drawing conclusions from data across applied business and/or scientific domains

• Technical proficiency in scientific computing and scripting in Python, along with demonstrated experience working with various database systems including SQL and NoSQL

• Deep expertise in diverse data science methodologies, including predictive AI

• Experience with generative AI, preferably with LLMs

• Demonstrated experience developing and deploying customized agentic AI applications

• Comfort presenting to and collaborating effectively with senior stakeholders across diverse functional areas

• Excellent written and verbal communication skills

Desirable Skills/Experience

• PhD in Mathematics, Computer Science, Engineering, Physics, Statistics, or a related quantitative field

• Experience in MLOps/LLMOps and CI/CD pipelines

• Experience with R

• Experience in clinical development

• Experience in a complex global organization

At AstraZeneca, work has a direct impact on patients, transforming how life-changing medicines are developed by combining leading science with powerful digital platforms and data. Teams are trusted to explore bold ideas, experiment with the latest technologies-from AI agents to modern data tooling-and tackle complex problems that have often never been solved before. Colleagues learn from one another across disciplines and backgrounds, supported by investment in tools, platforms and development opportunities such as hackathons, mentoring and coaching. It is a fast-paced environment where diverse perspectives are valued, collaboration spans functions and geographies, and every contribution helps the business make better decisions for patients worldwide.

If this role sounds exciting and the opportunity to shape the future of data-driven drug development inspires you,