Senior Principal Scientist, Real-World Evidence (RWE) Full-time NEW

Senior Principal Scientist, Real-World Evidence (RWE)

Johnson & Johnson Innovative Medicine is recruiting for R&D Data Science and Digital Health, Senior Principal Scientist, Real-World Evidence (RWE). This position has a primary location of Titusville, NJ but is also open to Spring House, PA; Cambridge, MA; or La Jolla, CA.

Johnson & Johnson Innovative Medicine develops treatments that improve the health of people worldwide. Research and development areas encompass oncology, cardiovascular and metabolic disorders, immunology, pulmonary hypertension, retinal disorders, and neuroscience. Our goal is to help people live longer, healthier lives. We have produced and marketed many first-in-class prescription medications and are poised to serve the broad needs of the healthcare market – from patients to practitioners and from clinics to hospitals.

The R&D Data Science RWE team within Johnson & Johnson Innovative Medicines develops innovative insights and solutions bringing to bear a variety of different data sources across multiple disease areas. We are looking for outstanding scientist and leader whose responsibilities include:

• Be a hands-on technical leader, leading a portfolio of RWE projects while instituting best practices, and developing common technical tools, crafting a data-driven culture, of accelerating, scaling and prodcutionalizing deliverables while mentoring and educating peers in the adoption of technical best practices and common tools.
• Identify common technical requirements for RWE projects, develop and maintain a common suite of tools that enables RWE data scientists to accelerate delivery and scale common deliverables.
• End-to-end expertise in RWE studies including conceptualizing the research questions, data feasibility, study design, analysis, programming, and interpretation.
• Provide thought leadership and hand-on programming expertise for developing, adapting and delivering Real-World Data (“RWD”) methodologies to mitigate observed and unobserved bias and confounding in the execution of comparative effectiveness analyses, time-to-event analyses, external control arm studies, hybrid control arm studies, retrospective and prospective study designs.
• Provide thought leadership and hand-on programming expertise to generating RWE or secondary evidence from post-hoc RCT analyses, observational databases, and literature reviews to support regulatory agency interactions.
• Independently create study protocols, statistical analysis plans, and statistical programming deliverables including analysis-ready data, tables, and figures using appropriate statistical analysis software while instituting best practices for execution across the broader team.
• Experience creating pipelines, functions, packages to perform frequently used actions and/or deliverables across broad group of stakeholders.
• Partner with the Data Science Therapeutic Area scientists to conceptualize, lead, shape and deliver Real World Evidence, and advanced analytics solutions and insights for prioritized use cases taking ownership of one or more disease area evidence generation teams.

Required qualifications:

• A Ph.D. degree, or master's degree in a quantitative field (e.g., epidemiology, statistics, biostatistics, or similar)
• At least 5 years of relevant experience within start-up, technology, biopharma or healthcare industries, or highly relevant academic experience, on a case-by-case basis
• Extensive hands-on experience with data engineering and exploratory data analysis, statistical modeling, time-to-event analyses, comparative effectiveness analyses, causal inference methods to mitigate observed and residual confounding (e.g., propensity score matching/weighting, instrumental variables, state transition models)
• Demonstrated expertise with multiple real-world data sources (EHR, insurance claims, registry data). Familiarity with data structure and programming of clinical trial data
• Excellent interpersonal, communication and presentation skills
• Extensive experience with database programming and use of statistical programming languages including expert proficiency in either, R or Python working proficiency in SAS and SQL
• Demonstrated experience as a technical lead in developing, testing and maintaining technical frameworks for RWE analyses
• Extensive knowledge of RWE Common Data Models (OMOP, FHIR, i2b2) & Analysis frameworks (OHDSI, pharmaverse)

Preferred qualifications:

• Familiarity with drug discovery and the clinical development process
• Expertise in oncology, Immunology or Neuroscience drug development
• Experience in regulatory-grade evidence, communicating and responding to agency reviews and comments.