Senior Data Sciencist - AI & Scientific Applications

Johnson & Johnson Johnson & Johnson · Pharma · Madrid, Spain +1

Senior Data Scientist role focused on designing, building, testing, and deploying AI solutions, including LLMs and RAG, for scientific and healthcare challenges. The role involves hands-on coding, data pipeline development, model integration, and a strong emphasis on AI quality through testing and evaluation. It aims to move prototypes into production and improve existing workflows for scientific literature search, evidence synthesis, and content generation.

What you'd actually do

  1. You will build applications that support scientific literature search, evidence synthesis, data exploration, study planning, and scientific content generation.
  2. You will write and review Python code, develop data pipelines, integrate AI models, troubleshoot technical issues, and help move prototypes into production.
  3. A key part of the role is AI quality.
  4. You will also guide technical decisions, review solution designs, mentor colleagues, and share practical knowledge across the team.

Skills

Required

  • Master’s 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.

Nice to have

  • 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.

What the JD emphasized

  • design, build, test, and deploy AI solutions
  • hands-on technical role
  • writing high-quality code
  • testing AI outputs
  • building scalable solutions
  • AI quality
  • create test sets, evaluation methods, benchmarks, and validation approaches

Other signals

  • building AI-powered applications
  • design, build, test, and deploy AI solutions
  • hands-on technical role
  • writing high-quality code
  • testing AI outputs
  • building scalable solutions
  • working with Large Language Models, Retrieval-Augmented Generation
  • develop data pipelines
  • integrate AI models
  • move prototypes into production
  • AI quality
  • create test sets, evaluation methods, benchmarks, and validation approaches