Principal Data Scientist, Health Informatics

About the Role:

• Own clinical data quality across claims, EHR, and ADT with deep fluency in FHIR, HL7v2, and C-CDA.
• Build, validate, and deploy production ML/AI models for risk stratification and care gap prediction.
• Apply health economics methods including risk adjustment, cost attribution, and quasi-experimental evaluation.

Minimum Qualifications:

• Hands-on fluency with claims, EHR, and ADT data and clinical terminologies (ICD-10, SNOMED CT, LOINC, RxNorm, CPT/HCPCS).
• Master's degree in Data Science, Biostatistics, Health Informatics, or related field.
• 7-8+ years of hands-on Python experience with data science and ML libraries and end-to-end ownership of production models.

Preferred Qualifications:

• PhD in health informatics, statistics, data science, or computer science.
• Experience integrating EHR/HIE data via TEFCA or CommonWell.
• Health economics experience with risk adjustment, utilization measurement, and peer-reviewed publications.

Why This Role Matters:

• Define and own clinical data quality standards across claims, EHR, and ADT.
• Build and ship production ML/AI models that translate clinical data into actionable predictions.
• Advance core DS and AI products with production-grade models and rigorous methods.