Senior Data Sciencist AI & Scientific Applications

Want to apply AI to real scientific and healthcare challenges

At Johnson & Johnson Innovative Medicine we are building AI-powered applications that help teams find evidence faster analyze scientific information at scale and reduce manual work in research and evidence-generation workflows.

We are looking for aSenior Data Scientistbased in Madrid or Milan to design build test and deploy AI solutions that combine machine learning large language models data engineering and software development. You will work closely with scientists medical experts product managers engineers and business stakeholders to understand their workflows challenges and unmet needs. Rather than simply implementing predefined requirements you will help shape solutions by translating complex scientific and business problems into practical technology capabilities including AI-powered approaches where appropriate.

This is a hands-on technical role for someone who enjoys solving complex challenges writing high-quality code testing AI outputs and building scalable solutions that deliver meaningful value in scientific and healthcare workflows.

What You Will Do

You will build applications that support scientific literature search evidence synthesis data exploration study planning and scientific content generation. This includes working with Large Language Models Retrieval-Augmented Generation prompt design APIs databases cloud services and enterprise data sources.

You will write and review Python code develop data pipelines integrate AI models troubleshoot technical issues and help move prototypes into production. You will also improve existing workflows by making them more accurate scalable maintainable and easier to test.

A key part of the role is AI quality. You will create test sets evaluation methods benchmarks and validation approaches that measure accuracy consistency reproducibility and robustness. You will document assumptions limitations and recommended use so teams can understand when and how to rely on AI-generated outputs.

You will also guide technical decisions review solution designs mentor colleagues and share practical knowledge across the team. We value people who can explain complex technical choices clearly and help others build better systems!

Required Experience and Skills

• Masters degree or PhD in Data Science Computer Science Statistics Engineering Bioinformatics Life Sciences or a related field.

• 5 or more years of experience building data science machine learning AI or analytics solutions.

• Strong Python programming skills.

• Experience building applications services or pipelines that run beyond proof of concept.

• Experience with Large Language Models Generative AI prompt design Retrieval-Augmented Generation or related AI architectures.

• Experience working with APIs databases cloud platforms and modern software development practices.

• Strong understanding of statistics machine learning data engineering and model evaluation.

• Experience working with large complex or messy datasets.

• Ability to turn ambiguous scientific or technical problems into practical implementation steps.

Preferred Experience and Skills

• Experience in healthcare pharmaceuticals biotechnology clinical research medical affairs or life sciences.

• Experience with MLOps CI/CD automated testing model monitoring or AI evaluation frameworks.

• Experience developing AI systems for regulated or quality-controlled environments.

• Familiarity with cloud-native applications containers orchestration frameworks or enterprise AI platforms.

• Experience contributing to scientific publications conference presentations or technical communities.

Why Join Us

We work on technical problems that this role you will help create AI applications that support scientific research reduce repetitive work and make evidence-generation workflows faster and more consistent.

We offer opportunities to learn from experts across science medicine data and technology while contributing to systems that are used in real-world healthcare and life sciences settings. We support continuous learning practical experimentation and collaboration across disciplines.

What You Will Help Deliver

• AI applications that reduce manual work in evidence generation workflows.

• More reliable methods for searching synthesizing and generating scientific information.

• Reusable technical components that help teams build faster.

• Tested and documented AI workflows that can be deployed monitored and improved over time.