Senior Frontier AI Researcher

AstraZeneca; Barcelona; On-site; EUR 100,000 - 150,000; Full time

Job summary

AstraZeneca plc in Barcelona is seeking an AI researcher to join the Frontier AI Research lab within the Enterprise AI unit. The role is based in Barcelona with an on-site commitment of three days a week and requires fluency in English.

You will leverage advanced quantitative, computational, and algorithmic expertise to develop scalable AI and data science solutions across AstraZeneca’s business areas.

Qualifications

• Bachelor’s, Master’s or PhD in Mathematics, Computer Science, Engineering, Physics, Statistics, Computational Sciences, or related quantitative discipline—or equivalent experience.
• Demonstrated skills in modern AI/data science approaches, including supervised/unsupervised learning and scalable models.
• Proficient programming in Python and/or R.
• Experience with high-performance computing or cloud-based environments.
• Experience in data analytics or developing tools to extract insights from data.
• Excellent written and verbal communication skills, business analysis, and ability to explain complex results to diverse stakeholders.

Responsibilities

• Develop, implement, and support AI/data science solutions—models, tools, and algorithms—for diverse scientific and business applications.
• Translate unstructured problems into data-driven analytical solutions.
• Collaborate with scientists, data scientists, engineers, and business teams to identify opportunities and deliver AI-driven insights.
• Research and develop new predictive models and algorithms, using techniques like classification, regression, NLP, image analysis, graph theory, deep learning, and recommender systems.
• Integrate and analyze data from multiple sources and modalities.
• Deploy and optimize AI solutions in production using HPC or cloud environments.
• Provide technical expertise in frameworks like TensorFlow, Keras, PyTorch, BERT, R, Python ensuring robust methodologies.
• Work within governance frameworks ensuring regulatory/compliance/quality alignment.
• Communicate findings and uncertainties to stakeholders; contribute to publications and knowledge sharing.
• Promote continuous learning and adoption of new AI methods.

Skills

AI/ML fundamentals

Python/R programming

Cloud/HPC experience

Data analytics

Communication

Education

Bachelor/Master/PhD in quantitative field

Tools

TensorFlow

Keras

PyTorch

BERT

R

Job description

Introduction to role

This role is based in Barcelona, with an on-site commitment of three days a week. Fluency in English is required.

The Frontier AI Research lab is a group of researchers working within the Enterprise AI unit. Working at the bleeding edge of AI and ML method you'll keep AZ at the forefront of AI in our industry. You will leverage advanced quantitative, computational, and algorithmic expertise to develop, deliver, and support scalable AI and data science solutions across AstraZeneca’s business areas.

This role applies both foundational and cutting-edge approaches in AI engineering and data science to extract insights, solve business and scientific challenges, and advance innovation using structured and unstructured data.

Work collaboratively across multidisciplinary teams, combining technical strength, domain awareness, and strong communication skills to generate value and help drive AstraZeneca’s scientific and business goals.

Accountabilities

• Develop, implement, and support AI computational and data science solutions—including modelling algorithms, machine learning models, and AI tools—tailored to diverse scientific and business application areas.
• Translate complex, unstructured business or scientific problems into appropriate data-driven analytical and computational solutions.
• Collaborate with cross-functional stakeholders—including scientists, data scientists, engineers, and business teams—to identify opportunities, understand challenges, and deliver impactful AI-driven recommendations and insights.
• Research and develop new predictive models, computational methods, and algorithms, applying techniques such as classification, regression, clustering, natural language processing (NLP), image analysis, graph simulation theory, deep learning, and recommendation systems as needed.
• Integrate, process, and analyze data from multiple sources and modalities to ensure comprehensive approaches to problem-solving.
• Deploy and optimize AI and data science solutions in production settings, leveraging high-performance computing or cloud environments as appropriate.
• Provide technical expertise or support in specialist AI and data science frameworks and packages (e.g., TensorFlow, Keras, PyTorch, BERT, R, Python), ensuring robust, scalable, and reproducible methodologies.
• Work within project parameters and governance frameworks, ensuring alignment with regulatory, evidential, compliance, and quality standards.
• Clearly and objectively communicate findings, uncertainties, and limitations to stakeholders, and contribute to scientific and business publications, presentation, or knowledge sharing.
• Promote continuous learning, awareness, and adoption of new methods, technologies, and best practices in AI science and engineering.

Essential Skills/Experience

• Bachelor’s, Master’s or PhD Degree—in Mathematics, Computer Science, Engineering, Physics, Statistics, Computational Sciences, or a related quantitative discipline—or equivalent experience.
• Demonstrated technical skills and experience in modern AI and data science approaches, including supervised and unsupervised learning, machine learning, pattern recognition, and the development of scalable classifiers or models.
• Proficient programming and software development skills, such as Python and/or R.
• Experience with high-performance computing or cloud-based environments.
• Demonstrated experience in data analytics or developing tools for understanding and extracting insights from data.
• Excellent written and verbal communication skills, business analysis, and ability to explain complex results to diverse stakeholders.

Desirable Skills/Experience

• Master’s or PhD in a relevant quantitative discipline.
• Proven record of publishing predictive modelling results, tools, or AI research in peer-reviewed journals, conferences, or other scientific proceedings.
• Prior experience in life sciences, healthcare, or drug discovery and development, especially in roles involving target discovery, indication discovery, or patient-disease stratification.
• Experience with regulatory and evidential requirements in scientific or clinical settings.

When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

Why AstraZeneca

Here, your AI research fuels real decisions and real therapies. You will work with modern platforms and diverse collaborators to tackle problems that span discovery science to enterprise operations, all while developing your craft through continuous learning and shared experimentation. We bring unexpected teams together, value kindness alongside ambition, and give you the autonomy and support to test, learn, and scale ideas that matter—so your contributions compound into impact for patients and the business.

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.