Senior RWD Data Scientist - Remote Precision Medicine

Tempus AI; Redwood City (CA); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Incentive compensation

Restricted stock units

Medical and other benefits

Job summary

Tempus AI is seeking a Senior Data Scientist focused on real-world data analytics (RWD) to advance precision medicine. You will design and validate clinical heuristics, maintain Python-based profiling, and ensure robust data quality across complex oncological datasets.

Collaborate with clinical SMEs, ML engineers, and data scientists to deliver ground-truth standards, evaluation metrics, and transparent reporting.

Qualifications

• Bachelor's or Master's degree in a related field.
• 4+ years of data science experience with real-world healthcare data.
• Proficiency in Python and advanced SQL for complex data querying.
• Experience with data quality frameworks and profiling tools.
• Familiarity with oncology data and EHR data structures preferred.

Responsibilities

• Heuristic Development: Design, implement, and validate heuristic rules for derived clinical concepts.
• Data Profiling & Monitoring: Maintain Python-based profiling pipelines.
• Data Quality Assurance: Build and execute data quality checks and adherence to schemas.
• Longitudinal Patient Cohorting: Design inclusion/exclusion funnels for real-world data initiatives.
• Cross-Functional Collaboration: Work with clinical SMEs, ML engineers, and data scientists to define ground truth and validation datasets.
• Documentation & Reporting: Maintain docs, configs, and metrics for data quality and evaluations.

Skills

Python

SQL

Data profiling

ETL pipelines

Statistical analysis

NLP outputs

Education

Bachelor's or Master's in CS/DS/Stats/Engineering

Tools

Matplotlib

Seaborn

Plotly

Tableau

Job description

Tempus AI is seeking a Senior Data Scientist focused on real-world data analytics (RWD) to advance precision medicine. You will design and validate clinical heuristics, maintain Python-based profiling, and ensure robust data quality across complex oncological datasets.

Collaborate with clinical SMEs, ML engineers, and data scientists to deliver ground-truth standards, evaluation metrics, and transparent reporting.