Director Real World Data Scientist (Billerica MA)

MerckBillerica, MA
Onsite

About The Position

The Director is a senior individual contributor and scientific authority responsible for shaping how real-world evidence is generated and used to inform high-impact development and regulatory decisions. This role combines deep statistical and quantitative expertise with strong scientific judgment to define key questions, evaluate methodological choices, and ensure outputs are credible, defensible, and decision-grade. The Director plays a critical role in identifying methodological gaps, advancing approaches, and integrating perspectives across disciplines.

Requirements

  • 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.

Nice To Haves

  • 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.

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.

Benefits

  • health insurance
  • paid time off (PTO)
  • retirement contributions
  • other perquisites
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