Director Real World Data Scientist (Billerica MA)

Key Responsibilities

• Define key scientific questions underpinning evidence strategies.
• Provide leadership on RWE approaches supporting development and regulatory decisions.
• Serve as a recognized scientific authority on complex methodological topics.
• Identify methodological gaps, risks, and opportunities, and define pragmatic forward paths.
• Critically evaluate study designs, analytical strategies, and data sources.
• Apply deep expertise in statistical theory, bias, confounding, causal inference, and quantitative modeling.
• Assess whether methodological choices are fit-for-purpose, transparent, and scientifically defensible.
• Guide complex methodological decisions involving multiple sources of evidence and competing analytical options.
• Translate complex analysis into high-impact, decision-relevant insights.
• Shape evidence used to inform critical questions such as disease characterization, comparator strategy, endpoint feasibility, external control design, and patient population definition.
• Influence how evidence is generated and used in high-stakes decisions across programs.
• Evaluate emerging methodologies, technologies, and data paradigms for relevance and impact.
• Evaluate and guide how real-world data sources are selected, structured, and interpreted to support complex evidence needs.
• Apply deep understanding of data-generating processes and data limitations to inform methodological choices.
• Shape how data is made accessible, interpretable, and usable for evidence generation across teams.
• Provide scientific input into data pipelines, transformations, and analytical workflows to ensure they align with study needs and methodological rigor.
• Partner with data science and engineering functions to ensure data infrastructure supports high-quality, scalable, and reproducible analysis.
• Integrate innovations where they meaningfully improve rigor, efficiency, or interpretability.
• Partner across clinical development, biostatistics, regulatory, medical, HEOR, and data science.
• Act as a bridge across disciplines, aligning scientific perspectives and decision needs.
• Influence without authority in a complex matrix environment.
• Engage externally to support scientific credibility and methodological advancement.
• Contribute to methodological discussions with regulators, collaborators, or scientific communities where appropriate.
• Support publications, presentations, or collaborations aligned with strategic priorities.

  Minimum Qualifications

  • PhD in statistics, biostatistics, epidemiology, applied mathematics, data science, or a related quantitative discipline.
  • 8 or more years of experience in real-world evidence, statistics, epidemiology, or related fields.
  • Deep expertise in statistical methods, causal inference, and analysis of complex healthcare data.
  • Strong understanding of real-world data, data-generating processes, and data limitations.
  • Experience supporting regulatory and development decisions with high-quality evidence.
  • Demonstrated ability to influence cross-functional teams and shape methodological direction.
  • Excellent communication skills and strong scientific leadership presence.

  Preferred Qualifications

  • Recognized scientific thought leadership in RWE, statistics, or a related field.
  • Track record of advancing or applying innovative methodologies in real-world settings.
  • Experience integrating diverse data sources and evidence types.
  • Proficiency in R, python, or other programming languages.
  • Experience engaging with regulators or external scientific communities on methodological topics.