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Salary: USD 100,000 - 150,000 / annual
Tempus is seeking a Data Scientist II to join the Real World Evidence (RWE) group within Life Sciences R&D. This role focuses on advancing precision medicine by leveraging real-world clinical data and AI to deliver actionable insights for pharmaceutical partners and physicians.
You will lead observational studies and derive insights from complex real-world clinical data using advanced statistical methods and cutting-edge AI tools. Key responsibilities include:
• Pharma Collaboration & Strategy: Partner with pharmaceutical collaborators to independently execute robust RWE research plans leveraging Tempus's multimodal platform to address key questions in trial design and outcomes research.
• Real World Data Expertise: Lead the derivation of complex real-world endpoints through extensive coding, demonstrating deep comprehension of Tempus clinical and molecular data structures while serving as an expert on methodological nuances and limitations of real-world data.
• Methodology & Platform Contribution: Stay current on methodological advancements in real-world studies (causal inference, survival analysis) and oncology guidelines (NCCN, clinical trials) to contribute to reusable code, internal packages, and best practices across collaborations.
• AI & LLM Innovation: Incorporate LLMs, agentic workflows, and other AI tools into daily workflows to accelerate code development, discovery, documentation, review, and insight generation.
• Scientific Interpretation & Communication: Interpret RWE analysis results, evaluate study limitations, and communicate complex methods and results to technical and non-technical stakeholders. Prepare internal reports, external deliverables, manuscripts, and conference materials.
• Cross-Functional Collaboration: Work with product, oncology, clinical abstraction, and real-world data science teams to enhance data quality, products, and analytical best practices.
REQUIREMENTS:
Education: PhD in epidemiology, biostatistics, data science, public health, or related field; OR Master's degree with 2+ years of additional work experience.
Technical & Statistical Proficiency:
- Proficiency with observational real-world healthcare data, including time-to-event methodologies (survival analysis)
- Proven expertise executing RWD analytical studies
- Proficient in R and SQL, especially statistical tools and packages
- Proficiency applying machine learning, LLM-based coding assistants (Claude Code, Copilot, Cursor), and agentic frameworks
- Adherence to good software engineering practices (version control, modular code, documentation)
Communication & Client Focus:
- Demonstrated experience interfacing with clients and presenting to diverse stakeholders
- Excellent written and verbal communication skills with strong project management abilities
- Ability to thrive in fast-paced, dynamic environments working with multidisciplinary scientists
Preferred: Pharma or drug development experience; clinical trial design (Phase II-III); analytical proficiency with claims, EHR, or registry data; practical experience configuring or adapting LLMs; knowledge of oncology guidelines (NCCN); biomarker or molecular data experience (genomics); cloud platform experience (AWS, BigQuery, GCP).
