AI Electronic Health Record Phenotyping Researcher

About the role

Responsibilities

• Build clinical NLP models extracting condition evidence from physician notes, discharge summaries, and radiology reports
• Design structured data feature engineering from ICD codes, CPT codes, lab values, and medication orders
• Implement phenotype validation framework assessing sensitivity and specificity against chart-reviewed gold standards
• Develop phenotype portability assessment measuring how algorithms transfer across health system EHR populations
• Create semi-automated phenotype refinement suggesting criteria modifications that improve validation metrics
• Collaborate with clinical informaticists and researchers on phenotype clinical validity assessment

Requirements

• 6+ years in clinical informatics, health data science, or clinical NLP with EHR phenotyping experience
• Deep understanding of clinical data structures: diagnosis coding, lab reference ranges, and medication databases
• Strong Python and clinical NLP skills with transformer-based clinical text processing
• Experience with HL7 FHIR, OMOP CDM, or i2b2 data standards
• Track record developing validated phenotyping algorithms used in published clinical research

Benefits

• Hybrid: 2 days Boston facility, 3 days remote
• Comprehensive health benefits
• $4,000 annual professional development budget
• Research publication support
• Equity participation

Keep exploring related roles

Use these topic pages to discover more roles in the same hiring cluster.