Principal Data Scientist, Health Informatics
Tasks
- Apply LLM and foundation model methods
- Apply fairness validation
- Build care gap prediction models
- Build risk stratification models
- Conduct health economics and outcomes analysis
- Create decision grade evidence
- Define clinical data quality standards
- Develop validate and deploy production ML models
- Ensure model calibration
- Estimate treatment effects
- Execute risk adjustment
- Map EHR data to clinical reality
- Measure utilization and costs
- Mentor junior data scientists
- Normalize and validate clinical data for modeling
- Perform data leakage prevention
- Run quasi experimental evaluation
- Set architectural tradeoffs
- Validate clinical face validity
Perks/Benefits
- 401k match
- Commuter benefits
- Life insurance
- Medical, vision, and dental coverage
- Paid time off
- Parental leave
- Professional development stipend
- Work from home stipend
Skills/Tech-stack
C-CDA | CI/CD | CPT/HCPCS | Cost attribution | Experiment tracking | Experimental evaluation | FHIR | Feature Store | Generative AI | HL7v2 | ICD-10 | LOINC | Language Models | Large Language Models | MLOps | MLflow | Machine Learning | Model Registry | Python | Quasi Experimental | Quasi Experimental Evaluation | Reproducible Workflows | Risk adjustment | RxNorm | SNOMED CT | Sagemaker Pipelines | Utilization Measurement
Education
Master of Engineering | Master of Science | Master of Science in Computer Science | Master of Science in Data Science | Master of Science in Health Informatics | PhD
Roles
Data Scientist | Principal | Principal Data Scientist | Scientist
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