Senior Data Analyst: Oncology Clinical Insights (Remote)

Tempus AI; South Carolina; On-site; USD 80,000 - 125,000; Full time

Benefits offered by this job

Benefits including incentive comp and 

RSUs and medical benefits

Job summary

Tempus is seeking an experienced Senior Data Analyst to design and execute clinical evidence studies that aim to advance precision medicine for cancer patients. You will build clinical data models using dbt and SQL, develop reports for central monitoring and KPI metrics, and create data automation pipelines to deliver analysis-ready data sets.

The role includes data integration across data marts and de-identification of PHI, with strong emphasis on clear, actionable insights.

Qualifications

• 5+ years of relevant work experience in Life Sciences or Healthcare analytics.
• Strong command of SQL and scripting languages (R or Python).
• Experience with BI tools such as Looker and data visualization.
• Experience in oncology, cancer genomics, or clinical trials.
• Ability to translate raw data into actionable insights and recommendations.
• Excellent communication with diverse audiences and ability to own deliverables.

Responsibilities

• Develop clinical data models using dbt and SQL aligned with business needs.
• Develop reports for central monitoring, KPI metrics, and visualization of study performance.
• Create data automation pipelines for data delivery and analysis-ready datasets.
• Assist integration across data marts and manage de-identification of PHI.
• Support code maintenance, validation, and documentation.

Skills

SQL

R/Python

Oncology focus

Data visualization

Data cleaning

Communication

Ownership

Tools

dbt

Looker

Job description

Tempus is seeking an experienced Senior Data Analyst to design and execute clinical evidence studies that aim to advance precision medicine for cancer patients. You will build clinical data models using dbt and SQL, develop reports for central monitoring and KPI metrics, and create data automation pipelines to deliver analysis-ready data sets.

The role includes data integration across data marts and de-identification of PHI, with strong emphasis on clear, actionable insights.