Senior Principal Scientist, Real-World Evidence (RWE)

Role Summary

Senior Principal Scientist, Real-World Evidence (RWE) at Johnson & Johnson Innovative Medicine. This role focuses on leading RWE studies and developing methodologies to support regulatory interactions and evidence generation across multiple disease areas. Primary location is Titusville, NJ, with options for Spring House, PA; Cambridge, MA; or La Jolla, CA.

Responsibilities

• Be a hands-on technical leader, overseeing a portfolio of RWE projects, instituting best practices, and developing common technical tools to accelerate, scale, and productionalize deliverables while mentoring peers.
• Identify common technical requirements for RWE projects and maintain a suite of tools to enable rapid delivery and scaling of deliverables.
• Provide end-to-end RWE study expertise, including conceptualizing research questions, data feasibility, study design, analysis, programming, and interpretation.
• Develop and deliver Real-World Data (RWD) methodologies to mitigate bias and confounding in comparative effectiveness analyses and related study designs.
• Generate 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 programming deliverables including analysis-ready data, tables, and figures using appropriate software.
• Create pipelines, functions, and packages to support frequently used actions across stakeholders.
• Collaborate with Data Science Therapeutic Area scientists to conceptualize and deliver Real World Evidence and advanced analytics solutions for prioritized use cases, leading one or more disease area evidence generation teams.

Qualifications

• Required: Ph.D. or master‚Äôs degree in a quantitative field (e.g., epidemiology, statistics, biostatistics, or similar).
• Required: at least 5 years of relevant experience in startup, technology, biopharma, healthcare, or relevant academia, evaluated case-by-case.
• Required: hands-on experience with data engineering, exploratory data analysis, statistical modeling, time-to-event analyses, comparative effectiveness analyses, and causal inference methods (e.g., propensity score methods, instrumental variables, state transition models).
• Required: experience with multiple real-world data sources (EHR, insurance claims, registry data) and familiarity with clinical trial data programming.
• Required: excellent interpersonal, communication, and presentation skills.
• Required: proficiency in R or Python, with working proficiency in SAS and SQL; experience as a technical lead for RWE analyses.
• Required: knowledge of RWE Common Data Models (OMOP, FHIR, i2b2) and 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 and responding to agency reviews and comments.