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.
The Outcomes Research team at Tempus partners with external Pharma, biotech and academic institutions to provide best in class data, analysis and methodological guidance to Tempus’s real world data offering. We are seeking a highly motivated and capable Sr. Data Scientist with extensive experience and interest in design and analysis of pharmacoepidemiological studies to join our team.
Responsibilities:
Lead and execute HEOR and RWE projects (e.g., outcomes analysis, treatment patterns, and 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.
Work 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 real world studies
Build infrastructure including reusable code
Comply with all applicable regulations and Company procedures
Required Experience:
Advanced degree (Masters with 5+ years of experience or PhD with 3+ years of experience) or Bachelor’s degree with 8+ years of experience in data science, bioinformatics, biostatistics, epidemiology, public health, or related fields.
Computational skills using R and SQL, specifically applied to large-scale healthcare datasets.
Ideal candidates will possess:
Strong data manipulation and analysis skills tailored to observational data.
Deep familiarity with HEOR and RWE methodologies, including techniques to address confounding (e.g., propensity score matching, inverse probability weighting).
Experience analyzing large, complex real-world datasets, including administrative claims, electronic health records (EHR), and clinico-genomic databases.
Strong communication and presentation skills, with the ability to effectively translate complex methodologies to non-technical stakeholders.
Self-driven mindset with the ability to tackle ambiguous problems and work well in interdisciplinary teams.
Experience with time-to-event analysis and survival methodology.
Experience working in oncology and/or analyzing outcomes specific to cancer genetics, immunology, or molecular biology.
Collaborative approach, an eagerness to learn, and a high-integrity work ethic.
Sharp attention to detail and 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 and software testing
Experience working in oncology Phase II-IV clinical trials and/or experience with the analysis of RWD studies (e.g. using claims, EHR or registry data sources)
Hands-on experience in helping to prepare regulatory submissions to the FDA
Experience supporting data science teams in model building and validation
Client facing or consulting experience and comfort with presenting results to stakeholders
The expected salary range above is applicable if the role is performed from Illinois and may vary for other locations (California, Colorado, 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.
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.
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