Impress employers and recruiters.
Choose from hundreds of resume examples.
Impress employers and recruiters.
Choose from hundreds of resume examples.
Tailor your resume to this Sr. Data Scientist, Outcomes Research role.
Rezi rewrites your resume against Tempus AI's job description. Free.
Tailor your resume to this Sr. Data Scientist, Outcomes Research role.
Rezi rewrites your resume against Tempus AI's job description. Free.
Don't guess if your resume is good enough.
See how it scores against the Sr. Data Scientist, Outcomes Research posting at Tempus AI — free, in seconds.
Don't guess if your resume is good enough.
See how it scores against the Sr. Data Scientist, Outcomes Research posting at Tempus AI — free, in seconds.
About the Role
Tempus' proprietary platform connects an ecosystem of real-world evidence to deliver 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 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.
Requirements
- 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.
- 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).
- 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.
Skills
- R
- SQL
- Causal inference
- Pharmacoepidemiologic methods
- Time-to-event analysis
- Survival methodologies
- Git
- Model building
- Feature engineering
- Performance assessment
Location
- Remote US
- NYC
- SF
- California
- Colorado
- Illinois
- New York
- Los Angeles
Work Type
- Remote
Experience Level
- Master’s with 5+ years experience
- PhD with 3+ years experience
- Bachelor’s with 8+ years experience
Education Level
- Master’s degree
- PhD
- Bachelor’s degree
Salary/Compensations
- $100,000-$160,000
- $115,000-$175,000
Benefits
- Incentive compensation
- Restricted stock units
- Medical and other benefits
About the Company
- 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.
Equal Opportunity
- 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.
- 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.