Sr. Data Scientist, Outcomes Research

Tempus AI • Boston, MA

1d • $100,000 - $175,000 • Remote

About The Position

Tempus is seeking a highly motivated and capable Senior Data Scientist to join its Outcomes Research team. The team partners with external pharmaceutical, biotechnology, and academic institutions to provide data, analysis, and methodological guidance for Tempus’s real-world data offering. The role focuses on designing and analyzing pharmacoepidemiologic and health economic outcomes research studies, and leading real-world evidence projects such as outcomes analyses, treatment-pattern studies, and healthcare resource utilization research.

The Senior Data Scientist represents Outcomes Research and works with internal and external stakeholders to design, analyze, interpret, and publish real-world studies. The position applies appropriate epidemiologic and health economic methods to complex problems, collaborates with scientists, engineers, and product developers to translate research into clinically actionable insights, and develops reusable analytical code, templates, and workflows. The role also requires staying current with methodological advances in real-world evidence and complying with applicable regulations, Tempus data governance, and company procedures for real-world data use and reporting.

Requirements

• An advanced degree in data science, bioinformatics, biostatistics, epidemiology, public health, or a related quantitative field: Master’s degree with 5+ years of experience, PhD with 3+ years, or Bachelor’s degree with 8+ years.
• Demonstrated computational skills using R and SQL, applied to large-scale healthcare datasets.
• Strong data manipulation and analytical skills tailored to observational and real-world data.
• Deep familiarity with HEOR and RWE methodologies, including methods to address confounding such as propensity score matching, weighting, and inverse probability of treatment weighting.
• Experience analyzing large, complex real-world datasets, such as administrative claims, electronic health records, or clinico-genomic databases.
• Strong communication and presentation skills, including explaining complex methodologies and findings to non-technical stakeholders.
• Self-directed approach and ability to address ambiguous problems and work effectively in interdisciplinary teams.
• Ability to draw appropriate inferences from study designs and explicitly assess and communicate study limitations.
• Collaborative working style, eagerness to learn, high-integrity work ethic, attention to detail, and commitment to high-quality, timely analytics.

Nice To Haves

• Experience with time-to-event analysis and survival methodologies.
• Experience in oncology or analyzing outcomes related to cancer genetics, immunology, or molecular biology.
• Experience with version control such as Git and with software testing or validation processes.
• Experience working in oncology Phase II–IV clinical trials or analyzing RWD studies 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.

Responsibilities

• Lead and execute health economics and outcomes research (HEOR) and real-world evidence (RWE) projects, including outcomes analyses, treatment patterns, and healthcare resource utilization.
• Represent the Outcomes Research function and collaborate with internal and external stakeholders in the design, analysis, interpretation, and publication of real-world studies.
• Apply judgment to select and adapt appropriate epidemiologic and health economic methodologies for complex problems.
• Partner with interdisciplinary teams of scientists, engineers, and product developers to translate research into clinically actionable insights for clients.
• Stay current with methodological advances in RWE, including causal inference and pharmacoepidemiologic methods.
• Build reusable analytical infrastructure, including code, templates, and workflows, to improve the speed and quality of engagements.
• Comply with applicable regulations, Tempus data governance, and company procedures concerning real-world data use and reporting.

Benefits

• Tempus offers a full range of benefits, which may include incentive compensation, restricted stock units, medical benefits, and other benefits depending on the position.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior