Senior Data Science

Senior Data Scientist – Johnson & Johnson

Join us to develop data science solutions that drive impact for patients and for Janssen at Johnson & Johnson Innovative Medicine.

Titusville, New Jersey, United States of America

Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow. Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.

The Commercial Data Sciences team within Johnson & Johnson Innovative Medicine Business Technology organization is looking for an extraordinary scientist who is passionate about crafting, developing, and fielding data science solutions that drive impact for patients and for Janssen. There are many ways to explore and analyze data, and this powers the excitement and passion of data scientists at Janssen as many business units are eager to use the data to build business value.

• Translating unstructured, complex business and clinical problems into appropriate data problems and analytical solutions using domain‑specific understanding of epidemiology and RWD.
• Staying current with methodological advances in analytics, observational research methods, causal inference, and RWD/RWE best practices; apply and evangelize best practices across the organization.
• Oversee data curation, linkage and quality assessment across diverse RWD sources (EHR/EMR, claims, registries etc.) and ensure reproducibility and traceability of analyses.
• Develop effective relationships with commercial and medical leaders to ensure utilization and value of information resources and services in multiple projects.
• Responsible for advanced data science expertise to multiple cross‑functional projects and drive delivery of complex data science solutions that drive value to Johnson & Johnson.
• Lead and apply ongoing knowledge and awareness in trends, standard methodology and new developments in analytics and data science to influence functional practices.
• Collaborates across the Johnson and Johnson Data and AI community to develop best practices and cross functional opportunities that drive value.
• Oversight of partnerships with multiple third parties, academic or outsourced partners to shape and drive project outcomes and knowledge building.

• Ph.D. with 2+ years of experience, or M.S. with 3+ years of relevant pharma or healthcare experience, in Statistics, Epidemiology, Machine Learning & Artificial Intelligence, Computer Sciences, Physics, Molecular Biology, Bioinformatics, Computational Informatics, Medical Informatics, Computational Biology or a related discipline.
• 3+ years of hands‑on experience conducting observational research and RWE analyses using RWD across different therapeutic areas and diseases.
• Proven experience designing and leading RWE studies, including protocol and statistical analysis plan development.
• Strong expertise in causal inference and observational study methods (propensity scores, inverse probability weighting, instrumental variables, target trial emulation, sensitivity analyses).
• Experience with at least two of the following: statistical modeling, machine learning, deep learning, causal inference methods, multivariate regression and classification, large language model or forecasting.
• Track record of consistently delivering on high‑impact data science projects.
• Hands‑on experience with Python or R, and SQL or PySpark.
• Experience with at least one of the following cloud computing platforms: AWS Sage Maker, Azure, or Databricks, etc.
• Experience with visualization tools such as Tableau or Power
  
  BI, etc.
• Must have an understanding and the ability to interpret ML, quantitative methods applied to real‑world data.
• Ability to understand, shape, and measure the business value of solutions, while managing competing stakeholder priorities and ambiguity.
• Enthusiastic about building on and learning new methods and ways to use real world data to change the practice of medicine.
• Stro…