Director, Epidemiology & Methodological Innovation

Tempus AI · Vertical AI · Chicago, IL

Director of Epidemiology & Methodological Innovation to lead high-impact research for biopharma partners, focusing on developing and validating novel epidemiological methods using multimodal datasets (clinical, molecular/genomic) and applying causal inference and machine learning techniques. This role involves client-facing strategy, scientific thought leadership, and bridging data science with productization, with a strong emphasis on regulatory-grade insights for drug development.

What you'd actually do

  1. Methodological Innovation: Lead the development of novel approaches for RWE, including the use of external control arms (ECA), causal inference in high-dimensional data, and the integration of longitudinal clinical data with molecular/genomic signatures.
  2. Research Design & Implementation: Oversee the end-to-end execution of retrospective database analyses. You will act as the primary architect for study protocols, ensuring they push the boundaries of current HEOR/RWE standards while maintaining scientific rigor.
  3. Scientific Thought Leadership: Serve as a subject matter expert for biopharma clients, advising them on "first-in-kind" study designs. You are expected to contribute to the broader scientific community through high-impact publications and presentations at conferences like ISPOR, ISPE, and ASCO.
  4. Client Strategy & Partnership: Partner with Key Account Directors and Business Development to identify opportunities where novel methodology can solve "unsolvable" client problems (e.g., rare disease characterization or complex biomarker validation).
  5. Cross-Functional Synergy: Bridge the gap between Data Science, Biostatistics, and Product teams to productize successful novel methods, ensuring they are scalable across the Tempus ecosystem.

Skills

Required

  • PhD or PharmD in Epidemiology, Biostatistics, Health Economics, or a related quantitative field
  • 7+ years in HEOR/RWE
  • 3+ years in a leadership capacity
  • Deep expertise in oncology
  • Proven track record of developing or implementing advanced methods (e.g., target trial emulation, propensity score applications in complex cohorts, or machine learning-augmented epidemiology)
  • Advanced skills in R or SAS
  • Experience working with "messy" real-world data (EHR, claims, and/or genomic data)
  • Exceptional ability to simplify complex methodological hurdles into a clear strategic roadmap
  • Demonstrated experience mentoring junior scientists and leading cross-functional squads

Nice to have

  • Experience with external control arms (ECA)
  • Experience with longitudinal clinical data integration
  • Experience with molecular/genomic signatures

What the JD emphasized

  • develop and validate novel epidemiological methods
  • multimodal datasets
  • regulatory-grade insights
  • causal inference
  • machine learning-augmented epidemiology
  • messy real-world data
  • stringent regulatory and ethical standards (e.g., GEP, HIPAA)

Other signals

  • develop and validate novel epidemiological methods
  • unlock the full potential of Tempus’s multimodal datasets
  • integrate longitudinal clinical data with molecular/genomic signatures
  • machine learning-augmented epidemiology