Responsibilities
Job ID R-253184 Date posted 06/01/2026
Benefits
We're driven by our shared values of serving people, society and the planet. Our people make this possible, which is why we prioritise diversity, inclusivity, balance and sustainability. Discover what a career at AstraZeneca could mean for you.
An award-winning company
We're passionate about being a great place to work, and 84% of our employees would recommend us as an employer. We've been recognised as a Top Employer in Spain, an EFR Family Responsible Business, and we achieved third place in Forbes Spain's Top 50 Best Places to Work list.
Inclusive environment
Diversity and inclusion are embedded in everything we do, and our different views, experiences and strengths enrich our culture. There's no salary gap at AstraZeneca, and the number of female employees has increased by four per cent over the last three years. We've also made all positions fully accessible.
Work-life balance
Your wellbeing means a lot to us, and we're here to support you through all of life's ups and downs. That's why we offer an unpaid leave policy, annual leave, reduced-hours timetables and a host of benefits, including a retirement plan, long service award, and health and travel insurance.
Sustainability initiatives
We're committed to harnessing the power of science to become a more sustainable business. We've reduced our carbon footprint by over 9,000 kg of CO2 over the last two years, and we lead the European GoGreen Project, which aims to introduce environmentally friendly options in our fleet of corporate vehicles.
About the company
- Design and implement AI agentic workflows and advanced machine learning models to solve complex healthcare problems.
- Translate analytical prototypes into robust, scalable production systems.
- Lead end-to-end ML lifecycle from data preparation to deployment and monitoring.
- Develop and maintain data pipelines supporting model training and deployment.
- Deliver production ready code as well as infrastructure as code, implementing best practices for code quality, testing, and documentation.
- Collaborate with cross-functional teams to deliver data-driven solutions.
- Mentor team members with a less technical background in software engineering.
- Collaborate in a multidisciplinary environment to align AI initiatives with business objectives and drive digital transformation.
- Stay current with advancements in data science, AI and software engineering.
- Degree in Computer Science, Mathematics, Physics or related quantitative field.
- 5+ years in data science roles focused on production-ready solutions.
- Strong Python programming with proficiency in data science libraries such as NumPy, pandas, scikit-learn, SciPy, Optuna and TensorFlow/PyTorch.
- Extensive experience developing and deploying Python APIs, particularly using FastAPI and MCPs.
- Agentic AI frameworks for design and orchestration.
- Strong expertise in Python testing frameworks (pytest, unittest, mock)
- Experience with RESTful API design, documentation, dependency injection, error handling, and logging.
- Proficiency with AWS cloud services (CDK, EKS, S3, IAM, CloudWatch)
- CI/CD experience, particularly with GitHub Actions workflows.
- Advanced SQL skills and experience with graph databases.
- Docker containerization and Kubernetes orchestration experience.
- Experience working with AI tools and Large Language Models (LLMs) for practical applications.
- Creative problem-solving abilities and outside-the-box thinking.
- Excellent communication skills for technical and non-technical audiences.
- Proven collaborative team experience.
- Demonstrated innovation mindset and ability to work independently.
- AWS Machine Learning Engineer or AWS Solution Architect certification.
- TypeScript or a similar strongly-typed programming language experience.
- Data visualisation expertise.
- Experience with real-time data processing and streaming.
- Performance testing experience with data-intensive applications.
- Front-end development familiarity.
- Knowledge of healthcare AI/ML regulatory requirements.
- Knowledge of drug development and previously experience of working in pharmaceutical industrial.