Job description

Passionate about precision medicine and advancing the healthcare industry? Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time. About Tempus and the Outcomes Research Team Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus’ proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time. The Outcomes Research team partners with external Pharma, biotech, and academic institutions to provide best-in-class data, analysis, and methodological guidance for Tempus’s real-world data (RWD) offering. We are seeking a highly motivated and capable Sr. Data Scientist with extensive experience in the design and analysis of pharmacoepidemiologic and health economic outcomes research (HEOR) studies. 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. Required Qualifications: Advanced degree (Master’s with 5 years experience, PhD with 3 years experience, or Bachelor’s with 8 years experience) in data science, bioinformatics, biostatistics, epidemiology, public health, or a related quantitative field. Demonstrated computational skills using R and SQL, specifically applied to large-scale healthcare datasets. Preferred Qualifications: 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, such as 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. Nice to Have: Experience with version control (e.g., Git) and software testing or validation processes. Experience working in oncology Phase II–IV clinical trials and/or analysis of RWD studies (e.g., claims, EHR, 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. Remote US: $100,000-$160,000 NYC/SF: $115,000-$175,000 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. Additionally, for remote roles open to individuals in unincorporated Los Angeles – including remote roles- Tempus reasonably believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment: engaging positively with customers and other employees; accessing confidential information, including intellectual property, trade secrets, and protected health information; and appropriately handling such information in accordance with legal and ethical standards. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Requirements

Must-haves

Passionate about precision medicine and advancing the healthcare industry?
About Tempus and the Outcomes Research Team
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.
Demonstrated computational skills using R and SQL, specifically applied to large-scale healthcare datasets.
We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Nice-to-haves

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, such as 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 analysis of RWD studies (e.g., claims, EHR, registry data sources).

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aisql

Platform: workday
Effort: long