
Biotechnology Research · 3k people
Data Scientist II, Outcomes Research
Posted 26 Oct
What’s this role about? Lead and execute HEOR and real-world evidence projects in collaboration with external partners and internal stakeholders. Develop analytical infrastructure and translate complex research findings into clinically actionable insights for clients.
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Company
About Tempus AI Tempus is making precision medicine a reality by applying AI in healthcare, deriving insights from our expansive library of clinical data and molecular data. We enable physicians to make real-time, data-driven decisions to deliver personalized care and targeted therapies for patients through our analytical machine learning platform that uses the power of artificial intelligence in healthcare. We also work with partners to facilitate discovery, development, and delivery of optimized therapeutic options for patients through distinctive solution sets. Our mission is for each patient to benefit from the treatment of others who came before by providing the healthcare industry tools that learn as we gather more data. It’s About Time. For more information, visit tempus.com.
Tempus AI
Tempus AI, Inc. (NASDAQ: TEM) is a technology company leading the adoption of AI to advance precision medicine.

Responsibilities
- Lead and execute HEOR and real-world evidence (RWE) projects (e.g., outcomes analysis, treatment patterns, healthcare resource utilization) with external Pharma, academic, and other partners.
- Represent the Outcomes Research function and collaborate with internal and external stakeholders in the design, analysis, interpretation, and publication of real-world studies.
- Work on complex problems, exercising judgment in selecting and adapting appropriate epidemiologic and health economic methodologies.
- Partner with interdisciplinary groups of scientists, engineers, and product developers to translate research into clinically actionable insights for our clients.
- Stay current with the latest methodological advances in RWE, including causal inference and pharmacoepidemiologic methods.
- Build analytical infrastructure, including reusable code, templates, and workflows that improve speed and quality across engagements.
- Comply with all applicable regulations, Tempus data governance, and company procedures related to real-world data use and reporting.
Qualification
Required
- 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.
Preferred
- Strong data manipulation and analytical skills tailored to observational/real-world data.
- Deep familiarity with HEOR and RWE methodologies, including approaches to address confounding (e.g., propensity score matching, weighting, inverse probability of treatment weighting).
- Experience analyzing large, complex real-world datasets, including administrative claims, electronic health records (EHR), and/or clinico-genomic databases.
- Strong communication and presentation skills with the ability to translate complex methodologies and findings for non-technical stakeholders.
- Self-driven mindset with demonstrated ability to tackle ambiguous problems and work effectively in interdisciplinary teams.
- Experience with time-to-event analysis and survival methodologies.
- Experience working in oncology and/or analyzing outcomes related to cancer genetics, immunology, or molecular biology.
- Collaborative working style, eagerness to learn, and high-integrity work ethic.
- Sharp attention to detail and a passion for delivering high-quality, timely analytics.
- Ability to draw appropriate inferences based on study design and explicitly assess and communicate study limitations.
- Experience with version control (e.g., Git) and software testing or validation processes.
- Experience working in oncology Phase II-IV clinical trials and/or experience with the analysis of RWD and/or HEOR studies (e.g. using claims, EHR or registry data sources).
- Hands-on experience contributing to regulatory submissions to the FDA or other health authorities.
- Experience supporting data science teams in model building and validation, including feature engineering and performance assessment.
- Client-facing or consulting experience and comfort presenting results and recommendations to external stakeholders.
- #LI-BL1
- CHI: $90,000-$135,000 NYC/SF: $100,000-$150,000
- The expected salary range above is applicable if the role is performed from California and may vary for other locations (Colorado, Illinois, New York). Actual salary may vary based on qualifications and experience. Tempus offers a full range of benefits, which may include incentive compensation, restricted stock units, medical and other benefits depending on the position.
Benefits
- Incentive compensation
- Restricted stock units
- Medical benefits
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