Responsibilities:
- 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 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.
Qualifications
- 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).