Principal Scientist – Data Science (rwe)

Johnson & Johnson Johnson & Johnson · Pharma · Madrid, Spain

Principal Scientist - Data Science (RWE) at Johnson & Johnson Innovative Medicine in Madrid, Spain. This role focuses on developing and deploying cutting-edge statistical/machine learning models using Real World Data (RWD) to gain insights into diseases, improve patient outcomes, and enhance clinical development. The position requires a Ph.D. or Master's degree in a quantitative field, extensive experience in statistical modeling or machine learning, and proficiency in Python/R and SQL. The role involves leading projects, collaborating with cross-functional teams, and mentoring junior scientists.

What you'd actually do

  1. Lead and contribute to the development of statistical/machine learning models in health and healthcare (e.g., disease identification, patient stratification, disease progression, clustering, simulations, forecasting) based on RWD that will provide key insights to our pipeline assets.
  2. Leverage emerging scientific and technological developments to generate new research ideas, solutions and initiatives using real-world data (electronic health records, clinical development data, insurance claims, registries, others).
  3. Deliver scalable analytical/machine learning solutions and insights to impact functions and therapeutic areas within R&D and participate in cross-functional collaborations with internal scientific and data science teams, and external companies.
  4. Shape internal and external collaborations and define the scope of research questions.
  5. Closely partner with the Data Science Therapeutic Area (DSTA) and Therapeutic Area (TA) teams to execute on the priorities, building a roadmap to deliver the projects and present to senior cross-functional leaders.

Skills

Required

  • Ph.D. degree, or master’s degree in a quantitative field (e.g., statistics, biostatistics, epidemiology, applied mathematics, artificial intelligence, computer science, or similar)
  • Relevant experience (2+ years for Ph.D., 4+ years for a master’s) within a start-up, technology, or healthcare industry
  • Extensive experience with one of the following: statistical modeling, clustering and classification, causal inference methods, simulation, machine learning, deep learning
  • Hands-on technical data analysis and machine learning modeling experience
  • Proven project leadership in complicated context, able to influence and engage the strategic and technical partners in a matrix organization.
  • Proven track record of consistently delivering on high impact data science projects.
  • Expert proficiency in Python or R, and SQL

Nice to have

  • Experience delivering on RWE projects using advanced predictive methodologies including machine learning
  • In-depth expertise in at least one of the following domains: EHR, clinical development data, insurance claims, or registry data
  • Familiarity with and exposure to drug discovery and clinical development processes with one or more of the following therapeutic areas: oncology, immunology, neuroscience, or specialty ophthalmology.
  • Experience working closely with healthcare subject matter experts.
  • Ability to effectively communicate technical work to a wide audience.

What the JD emphasized

  • Proven project leadership in complicated context, able to influence and engage the strategic and technical partners in a matrix organization.
  • Proven track record of consistently delivering on high impact data science projects.

Other signals

  • develop cutting-edge methodologies to develop RWD-based solutions to enable disease insights, improve patient outcomes, and enhance clinical development
  • Deliver scalable analytical/machine learning solutions and insights to impact functions and therapeutic areas within R&D
  • Be a hands-on technical leader among the Data Science team, helping institute best practices while crafting a data-driven culture, developing, and mentoring more junior members of the team