Data Modeler I

• Collaborate with cross-functional teams including medical oncologists, research scientists, and engineers to develop and maintain clinical data models.
• Translate customer needs and product requests into key concept definitions and business logic for complex models.
• Facilitate integration of data model into workflows, applications, and data deliveries.
• Structure and normalize data from a variety of sources, including Tempus curated data, EHR integrations, and lab systems.
• Develop and maintain knowledge bases for clinical concepts.
• Create and execute validation plans in conjunction with SMEs for new models and disease types.
• Proactively monitor and support quality assurance and process improvement initiatives.
• Monitor performance of production processes and recommend areas for improvement.

• 5+ years of oncology data modeling experience.
• Experience working with real world data from various sources (e.g., curation workflows, EHRs, lab systems, claims, research datasets).
• Experience working with modern ELT tools such as DBT to maintain high volume, high velocity data warehouses
• Experience working with standard medical terminologies (e.g., SNOMED CT, RxNorm, LOINC, ICD-9/10).

Nice-to-haves:

• Clinical background (MD/DO, PharmD, PA, NP, RN, etc.).
• Familiarity with next-generation sequencing data.
• Experience with real world data analysis in Python or R.
• Participation in professional organizations (e.g., OHDSI, AMIA).