Data Scientist, Real-World Outcomes & HEOR (Remote)

Tempus AI; Colorado; On-site; USD 100,000 - 150,000; Full time

Job summary

Tempus is seeking a senior data scientist to lead HEOR and real-world evidence projects, collaborating with pharma, academia, and internal teams. You will design analyses, apply pharmacoepidemiologic methods, and translate findings into actionable insights for healthcare decision makers.

The role requires expertise in RWE, time-to-event analyses, and experience with large healthcare datasets. Strong communication skills and interdisciplinary collaboration are essential.

Qualifications

• Advanced degree (Master's with 2+ years experience or equivalent) in data science, bioinformatics, biostatistics, epidemiology, immunology, public health, or related quantitative field.
• Demonstrated computational skills using R and SQL, specifically applied to large-scale healthcare datasets.

Responsibilities

• Lead and execute HEOR and real-world evidence (RWE) projects with external Pharma, academic, and other partners.
• Represent the Outcomes Research function and collaborate with internal and external stakeholders in design, analysis, interpretation, and publication of real-world studies.
• Work on complex problems, selecting and adapting epidemiologic and health economic methodologies.
• Partner with interdisciplinary groups 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, including reusable code, templates, and workflows to improve speed and quality across engagements.
• Comply with all regulations, Tempus data governance, and company procedures relevant to real-world data use.

Skills

R

SQL

Education

Advanced degree (Master's or equivalent) in data science or related field

Job description

Tempus is seeking a senior data scientist to lead HEOR and real-world evidence projects, collaborating with pharma, academia, and internal teams. You will design analyses, apply pharmacoepidemiologic methods, and translate findings into actionable insights for healthcare decision makers.

The role requires expertise in RWE, time-to-event analyses, and experience with large healthcare datasets. Strong communication skills and interdisciplinary collaboration are essential.