Clover Health
Healthcare
DataAnalyst,ClinicalDataEffectiveness
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Data Analyst, Clinical Data Effectiveness at Clover Health. Skills: Clinical data, Data analysis, Interoperability standards. Identify and monitor healthcare facilities. Locate and quantify data gaps”
Industry & Context.
Root cause analysis
What They're Looking For.
Must Have
2+ years of hands-on data analytics experience, Direct exposure to healthcare data interoperability, Hands-on experience with healthcare data standards: HL7, CCDA, and ADT messages, Proficiency in SQL, Comfort working with large, complex datasets, Background in analyzing interoperability networks or HIE integrations, Skilled at data visualization, Investigative mindset, Self-directed, Able to manage multiple analytical projects
Nice to Have
Experience with TEFCA/QHIN frameworks, Familiarity with vendor-specific data exchange platforms, Background in value-based care, Background in population health, Background in clinical data operations, Experience with claims-clinical data reconciliation, Comfort working with Python or similar tools for data manipulation and automation
What You'll Do.
Identify and monitor healthcare facilities
Locate and quantify data gaps
Conduct deep-dive analyses
Map and correlate facility-specific data
Uncover systematic patterns of missingness
Establish and maintain reporting on ADT coverage
Recommend and guide implementation of technical configurations
Conduct evaluations and proof-of-concepts for new data integration
Determine existence and completeness of documentation
Develop a data-driven framework for prioritizing facility targets
and technical feasibility
Inform and guide vendor strategy
Ensure Counterpart Health is positioned for compliant
Define data requirements
Implement reliable pipelines
Validate data quality and clinical utility
Identify and remove operational and technical bottlenecks
and reliable clinical data flow
How You'll Work.
Team & Collaboration
Cross-functionally with Product Managers; With Engineers; With Clinical teams
Communication Scope
Present complex findings
Full Job Description
Counterpart Health is an AI‑powered physician enablement platform that delivers clinical insights to providers at the point of care. Our flagship product, Counterpart Assistant, is embedded into clinicians’ workflows and integrates with EHR systems, helping care teams drive value-based outcomes, close care gaps, and proactively manage chronic disease. As we grow our data ecosystem, expanding across legacy interoperability networks, QHIN/TEFCA connectivity, and direct HIE integrations, we need rigorous analytical ownership to ensure the clinical data powering our platform is complete, reliable, and actionable. You will serve as the Subject Matter Expert (SME) for clinical data completeness and effectiveness at Counterpart Health. Sitting within the Data Products pillar, this role owns the end-to-end understanding of our clinical data lifecycle: where data comes from, where it breaks down, and how each vendor or integration pathway performs across our customer markets. Your analysis will directly shape vendor strategy, facility targeting, and data pipeline investments, thus ensuring that the clinical evidence our care teams depend on is consistently available and trustworthy. As a Data Analyst, you will: Proactively identify and monitor which healthcare facilities consistently generate high-quality, usable clinical documents (e.g., EHRs, discharge summaries, procedure notes) to precisely locate and quantify data gaps. Conduct deep-dive analyses by mapping and correlating facility-specific data across disparate sources like structured claims, clinical care summaries (CCDAs), and ADT messages to uncover systematic patterns of missingness, latency, Experience with TEFCA/QHIN frameworks and evolving national interoperability standards. Familiarity with vendor-specific data exchange platforms (e.g., Bamboo Health, HSX, Particle Health, Kno2). Background in value-based care, population health, or clinical data operations. Experience with claims-clinical data reconciliation
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