Senior Clinical Data Analyst - Oncology Insights

Tempus AI; United States; Remote; USD 80,000 - 125,000; Full time

Benefits offered by this job

Medical benefits

Stock options

Incentive compensation

Job summary

Tempus AI in the United States is seeking a Senior Data Analyst to design and execute clinical evidence studies aimed at personalized cancer care. You will work with dbt and SQL to build data models and deliver analysis-ready datasets.

You will develop reports for monitoring KPIs, visualize study performance, automate data delivery pipelines, and support data integration across data marts while maintaining de-identification of protected health information.

Qualifications

• 5+ years of experience in analytics within Life Sciences or Healthcare.
• Strong SQL and scripting (R or Python).
• Experience with Looker BI and data visualization.
• Experience with disorganized data and turning it into actionable insights.
• Ability to manage multiple projects and deliverables with strong communication.

Responsibilities

• Develop clinical data models using dbt and SQL based on business need and interoperability between data models and delivery requirements.
• Develop reports for central monitoring, KPI metrics, visualization of study performance.
• Develop data automation pipelines for data delivery and data handling for analysis-ready datasets.
• Support integration of data across data marts and de-identification of protected health information.
• Maintain code quality, validation, and documentation.

Skills

SQL

R/Python

Looker

Oncology knowledge

Data visualization

Data cleansing

Communication

Independent work

Tools

dbt

Looker

Job description

Tempus AI in the United States is seeking a Senior Data Analyst to design and execute clinical evidence studies aimed at personalized cancer care. You will work with dbt and SQL to build data models and deliver analysis-ready datasets.

You will develop reports for monitoring KPIs, visualize study performance, automate data delivery pipelines, and support data integration across data marts while maintaining de-identification of protected health information.