Role based in Barcelona 3 days at office / 2 days at home

You will join a team that embraces a digital mindset and treats data as a core asset. From day one, you will contribute to high-priority projects where evidence quality, reproducibility and impact matter. As your solutions mature, you will see them adopted across programs and scaled to deliver measurable outcomes for patients and the business.

Accountabilities:
- Problem Framing and Hypothesis Development: Translate unstructured scientific and business problems into well-defined data problems, analytical approaches and testable hypotheses.
- Advanced Modelling and AI Research: Develop and implement models and methods across classification, regression, clustering, LLMs and simulation to interrogate clinical and business datasets within defined project scope.
- Decision Support and Insight Generation: Build predictive models and computational methods that guide decision-making, communicating results with appropriate uncertainties and limitations within agreed frameworks.
- Multimodal Data Integration: Integrate and process data from multiple sources and modalities to enable robust, scalable analyses that drive tangible value.
- Stakeholder Partnership: Build effective relationships with project managers, cross-functional peers, and scientific collaborators to ensure solutions are understood, trusted and used.
- Communication and Dissemination: Clearly and objectively present findings to technical and non-technical audiences; where appropriate, contribute to publications or conferences.
- Software Engineering and Compliance: Develop, implement and maintain tools and algorithms using a software engineering approach that meets regulatory and evidential requirements within established governance.
- Cross-Functional Contribution: Provide data science support to matrixed projects, executing defined solutions that deliver measurable outcomes for AstraZeneca.

Essential Skills/Experience:
- Bachelors Degree (or equivalent years of experience) in Mathematics, Computer Science, Engineering, Physics, Statistics, Economics, Computational Sciences, or a related quantitative discipline; or equivalent experience
- Experience in modern data science approaches, including unsupervised and supervised classification and regression algorithms such as k-means clustering, support vector machines, random forests, neural networks and deep learning.
- Demonstrated knowledge in advanced statistical modelling, or broader aspects of applied mathematics such as dynamical systems or optimisation.
- Understanding of algorithm design, development, optimization, scaling and applications
- Experienced in Python
- Excellent written and verbal communication, business analysis, and consultancy skills
- Familiarity with database systems (eg SQL, NoSQL, graph)

Desirable Skills/Experience:
- Masters Degree in Mathematics, Computer Science, Engineering, Physics, Statistics, Economics, or a related quantitative discipline
- Comfortable working in high performance computing or cloud environment
- Experience with large datasets using distributed computing
- Experience working with real world data (RWD/RWE)

Why AstraZeneca:
Here, technologists and scientists work side by side to push boundaries-unexpected teams in the same room unleashing bold thinking that turns data into therapies faster. We are investing in the convergence of advanced analytics and biology, using leading tools and platforms to transform the patient journey from insight to impact. You will be trusted to take smart risks, supported by a collaborative culture that values kindness alongside ambition, and encouraged to learn, share and iterate at pace-so your ideas travel from prototype to practice where they can change lives.

Date Posted

03-jun-2026

Closing Date

17-jun-2026

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.