ResponsibilitiesCollaborate 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.Qualifications5+ 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-havesClinical 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).#J-18808-Ljbffr