Principal Scientist, Data Insights & Hypothesis Design

Tempus AI; California (MO); On-site; USD 165,000 - 225,000; Full time

Benefits offered by this job

Benefits package

Job summary

Tempus is seeking a Principal Scientist for Data Insights & Hypothesis Design to ensure scientific coherence of a multimodal data platform. You will bridge molecular science and scalable data engineering, with emphasis on reproducible science and AI applications in neurology and immunology.

Responsibilities include data prototyping, client-aligned data strategies, and cross-disciplinary leadership to scale terabyte-scale datasets while maintaining data integrity and scientific rigor.

Qualifications

• PhD in a quantitative, NGS-related discipline with 6+ years of industry experience.
• Deep expertise in at least one of oncology, neurology, or immunology.
• Experience building large-scale relational databases and production-grade models.
• Proficiency with Python or R for reproducible analysis.

Responsibilities

• Prototype data offerings within the Tempus Data Model and deliver production-ready specs.
• Translate client research objectives into clinico-genomic data strategies.
• Act as core scientific authority across the organization and evaluate datasets.
• Support expansion across neurology and immunology with scalable data insights.

Skills

Python

R

SQL

Data prototyping

Statistical analysis

Translational research

Data modeling

Domain expertise (oncology/neurology/免

Education

PhD in quantitative, NGS-related discipline

Tools

Relational databases

SQL data models

Job description

Tempus is seeking a Principal Scientist for Data Insights & Hypothesis Design to ensure scientific coherence of a multimodal data platform. You will bridge molecular science and scalable data engineering, with emphasis on reproducible science and AI applications in neurology and immunology.

Responsibilities include data prototyping, client-aligned data strategies, and cross-disciplinary leadership to scale terabyte-scale datasets while maintaining data integrity and scientific rigor.