Senior Principal Scientist, R&D ; RWE Advance Analytics; AA at J&J Family

Senior Principal Scientist, R&D Real-World Evidence (RWE) Advance Analytics (AA)

Preferred

Location:

Raritan / Titusville, NJ;
Cambridge, MA; or Spring House, PA. May consider remote work. Primary location:
Titusville, FL.

• 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, accelerating, scaling, and productionalizing deliverables while mentoring and educating peers in the adoption of technical best practices and common tools.
• End‑to‑end expertise in RWE studies including conceptualizing the research questions, data feasibility, study design, analysis, programming, and interpretation.
• Provide thought leadership and hands‑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 hands‑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.
• Partner closely with R&D DSDH Real‑World Evidence LT team to drive strategic and business planning, to take a leading role in facilitating cross‑functional operational initiatives, ensuring effective coordination and seamless execution to drive the overall success of Real‑World Evidence projects.
• Contribute to the development and implementation of best practices, process improvements, and innovative approaches that will further enhance the impact of the Real‑World Evidence team.
• Contribute to the development and implementation of RW data strategy by identifying and exploring new opportunities for data‑driven innovation to support business objectives.
• Partner with the Data Science stakeholders to lead and coordinate policy efforts to influence the regulatory acceptability of RWE in decision making.

• 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).
• Demonstrated experience in managing operations, with strong stakeholder…