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Role Description

This role is ideal for a medically trained, technically strong professional who enjoys digging into complex clinical datasets, making sense of messy source systems, and shaping how clinical concepts and workflows are represented in scalable data products.

• Own and drive clinical interpretation, discovery, and modeling of healthcare data from multiple source systems.
• Explore and query complex healthcare data sources (EHR/EMR data, imaging, waveforms/streaming inpatient data, and clinical text) to identify, validate, and map key data structures.
• Define and govern clinical vocabularies, phenotypes, and concept groupings; ensure datasets align with clinical reality and care delivery workflows.
• Guide selection and application of clinical terminologies and standards (e.g., ICD, SNOMED CT, LOINC, CPT) and support harmonization/mapping strategies across systems.
• Build and refine standardized clinical data models by reconciling disparate datasets and mapping source fields to shared ontologies/common data models.
• Partner closely with data science and engineering to validate clinical accuracy, interpretability, and appropriate downstream use.
• Create clear documentation and explain complex data structures, transformations, and informatics decisions to both technical and clinical audiences.
• Support analytic programming and data QA efforts (SQL-heavy; Python/modern analytics tooling a plus).
• Produce concise findings and recommendations on informatics approaches tailored to stakeholders with varying technical depth.

Qualifications

• Clinical + Informatics background (preferred)
• Healthcare provider background (MD/DO/NP) strongly preferred; alternatively an advanced degree in a relevant clinical field, or equivalent deep clinical-domain experience.
• Formal clinical informatics training or certification (e.g., fellowship, AMIA/ABMS pathway) or meaningful hands-on clinical informatics experience.

Requirements

• Hands-on clinical experience with strong understanding of real-world workflows and how care is captured in structured and unstructured data.
• Strong SQL fluency and comfort querying EHR data; familiarity with Python and/or modern data tooling is a plus.
• Expertise with clinical terminologies and data standards (e.g., LOINC, SNOMED CT, RxNorm, NDC, CPT/HCPCS) and common data models (e.g., OMOP or similar).
• Experience with major EHR platforms (e.g., Epic and/or Cerner) is a plus.

Working Style

• Strong written communication and documentation skills.
• Collaborative, cross-functional mindset; comfortable in fast-moving environments.
• Organized, outcomes-oriented, and able to juggle multiple initiatives without losing rigor.
• Startup/early-stage experience is helpful but not required.

Working Environment & Benefits

• Remote-first with flexible hours (with reasonable overlap for meetings).
• Collaborative, low-ego team with strong learning culture.
• Professional development support.
• Occasional travel for in-person team working sessions (roughly quarterly).