Senior Principal Data Scientist, Real World Evidence (RWE)

Role Summary

Senior Principal Data Scientist, Real World Evidence (RWE). The position is flexible with primary locations Titusville, NJ; Raritan, NJ; Spring House, PA; Cambridge, MA; or San Diego, CA, with potential for remote on a case-by-case basis. The Senior Principal Data Scientist will collaborate with strategic partners in R&D Data Science and Digital Health to develop and implement evidence and insights to improve patient outcomes and accelerate clinical development in Oncology, Immunology, or Neuroscience.

Responsibilities

• Be a hands-on technical leader, leading a portfolio of RWE projects while developing best practices and common technical tools
• Support the development of the R&D RWE strategy for the generation and utilization of RWE for our key pipeline assets
• End-to-end expertise in RWE studies (external control arm, novel endpoints, trial design optimization) including conceptualizing research questions, data feasibility, study design, analysis, programming, and interpretation
• Assess treatment patterns and unmet needs using RWE to inform asset positioning
• Ensure RWE generation aligned with regulatory requirements and scientific standards
• Identify evidence opportunities and develop innovative evidence programs to support early development, registration, and post-marketing phases
• Shape the selection of real-world data sources, establish data quality standards, and ensure data robustness and relevance for clinical research
• Lead and develop junior researchers and programmers in executing strategies to develop RWE from concept through publication
• Support regulatory interactions and meetings with scientific data packages and expertise

Qualifications

• A Ph.D. degree, or master’s degree in a quantitative field (e.g., epidemiology, biostatistics, statistics, or similar)
• Relevant experience (4+ years for Ph.D., 6+ years for a master’s) within biopharma companies, RWE consulting firms, or other relevant healthcare industries
• Extensive hands-on experience with data engineering and exploratory data analysis, statistical modeling, time-to-event analyses, comparative effectiveness analyses, causal inference methods
• Demonstrated expertise with multiple real-world data sources
• Expert proficiency in R and SQL
• Familiarity with data structure and programming of clinical trial data
• Strong communication and influencing skills, capable of inspiring teams and driving cross-functional alignment
• Highly motivated and intellectually curious, with strong executional rigor and a passion for solving complex challenges

Education

• Ph.D. in a quantitative field or master’s degree in a quantitative field (epidemiology, biostatistics, statistics, or similar)