Clinical Data Analyst
US (Remote)
Role Overview
We are seeking a Clinical Expert with deep knowledge of medical coding systems and exceptional SQL skills to support terminology coverage and completeness metrics across multiple domains. This role will involve hands-on data analysis, terminology evaluation, and strategic content expansion initiatives.
Key Responsibilities
Coverage & Completeness Analysis
Write and execute complex relational SQL queries to calculate domain-level coverage metrics (e.g., % completeness by domain).
Collaborate with SMEs to define numerator/denominator logic for coverage metrics.
Track and report progress on coverage improvements over time.
Domain Expertise
Oncology: Assess terminology coverage for cancer-related concepts, staging, biomarkers, and treatment protocols.
Rare Diseases: Evaluate coverage based on Mondo codes and identify gaps for synonyms and related concepts.
Terminology & Data Model
Work with IMO terminology data models, including IMO Concept DB and associated knowledge graphs.
Understand SNOMED CT hierarchical structures as represented in IMO databases.
External Data Evaluation
Analyze external sources (e.g., ClinicalTrials.gov) to identify inclusion/exclusion criteria and gaps in IMO content.
Prioritize clinical trials and assess opportunities for content expansion (e.g., biomarkers, prior treatment history).
Quality & Process Improvement
Perform feasibility assessments and recommend enhancements to terminology coverage.
Document processes and contribute to continuous improvement initiatives.
Required Skills & Qualifications
Clinical background (Physician, Nurse, or equivalent healthcare professional).
Strong understanding of medical coding systems: ICD, CPT, HCPCS, SNOMED CT, LOINC, RxNorm, NDC.
Exceptional SQL skills for relational database queries and data analysis.
Familiarity with electronic health records (EHRs) and clinical documentation.
Experience with terminology mapping and hierarchical structures.
Ability to evaluate external clinical data sources for content gaps.
Excellent analytical, communication, and documentation skills.
Preferred / Bonus Skills
Experience with IMO terminology and data models.
Knowledge of oncology and rare disease coding standards.
Exposure to NLP/AI concepts for clinical data enrichment.A
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