Real-World Outcomes Data Scientist II

Tempus AI; Sacramento (CA); A distancia; USD 120.000 - 170.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Remote-friendly

Competitive compensation

Descripción de la vacante

Tempus is seeking an experienced Outcomes Research professional to lead HEOR and real-world evidence projects with pharma, academic, and other partners. You will collaborate with interdisciplinary teams to translate research into clinically actionable insights from real-world data.

The role requires an advanced quantitative degree and strong R/SQL skills, with expertise in observational study designs, time-to-event analysis, and causal inference.

Formación

• Advanced degree (Master’s with 2+ years experience or equivalent) in data science, biostatistics, epidemiology, or related field.
• Demonstrated computational skills using R and SQL on large-scale healthcare datasets.

Responsabilidades

• Lead and execute HEOR and real-world evidence projects with pharma, academic, and other partners.
• Represent the Outcomes Research function in design, analysis, interpretation, and publication of real-world studies.
• Work on complex problems, applying epidemiologic and health economic methods.
• Collaborate with interdisciplinary teams to translate research into clinically actionable insights for clients.
• Stay current with methodological advances in RWE, including causal inference and pharmacoepidemiologic methods.
• Build analytical infrastructure and reusable code to improve speed and quality across engagements.

Conocimientos

R

SQL

Propensity score matching

Observational data analysis

Time-to-event analysis

Educación

Master’s degree in data science or related quantitative field

Herramientas

Git

Descripción del empleo

Tempus is seeking an experienced Outcomes Research professional to lead HEOR and real-world evidence projects with pharma, academic, and other partners. You will collaborate with interdisciplinary teams to translate research into clinically actionable insights from real-world data.

The role requires an advanced quantitative degree and strong R/SQL skills, with expertise in observational study designs, time-to-event analysis, and causal inference.