Data Analyst, Clinical Data Effectiveness

About the role

You will serve as the Subject Matter Expert (SME) for clinical data completeness and effectiveness at Counterpart Health, owning the end-to-end understanding of our clinical data lifecycle from source to application. This role involves proactively identifying and monitoring which healthcare facilities consistently generate high-quality, usable clinical documents such as EHRs, discharge summaries, and procedure notes to precisely locate and quantify data gaps. You will experience with TEFCA/QHIN frameworks and evolving national interoperability standards while navigating vendor-specific data exchange platforms like Bamboo Health, HSX, Particle Health, and Kno2. Your analysis will directly shape vendor strategy, facility targeting, and data pipeline investments to ensure clinical evidence is consistently available and trustworthy for care teams. You will establish and maintain clear, transparent reporting on ADT coverage across key geographic, organizational, and technological dimensions including by county, facility, and underlying EMR system. Based on rigorous analysis of data flow and quality, you will recommend and guide the implementation of optimal technical configurations for existing data vendors such as Bamboo Health, PCC, Experian, and HSX. You will also conduct comprehensive evaluations and proof-of-concepts for potential new data integration technologies like Kno2 versus Particle Health to assess viability, quality improvements, and strategic fit.

Key facts

What you'll do

• 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, or incongruence in clinical records.
• 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 (e.g., matching EOBs to clinical encounter records).
• Comfort working with Python or similar tools for data manipulation and automation.
• Establish and maintain clear, transparent reporting on ADT coverage across key geographic, organizational, and technological dimensions (e.g., by county, facility, and underlying EMR system).
• Based on rigorous analysis of data flow and quality, recommend and guide the implementation of optimal technical configurations for existing data vendors (e.g., Bamboo Health, PCC, Experian, HSX).
• Conduct comprehensive evaluations and proof-of-concepts for potential new data integration technologies (e.g., Kno2 vs. Particle Health) to assess viability, quality improvements, and strategic fit.
• Systematically determine the existence and completeness of documentation associated with specific patient visits or encounters.
• Develop a data-driven framework for prioritizing facility targets for direct data acquisition, assessing impact, cost-effectiveness, and technical feasibility.
• Inform and guide vendor strategy around national initiatives such as TEFCA and QHIN adoption, ensuring Counterpart Health is positioned for compliant, high-quality data exchange.
• Partner cross-functionally with Product Managers to define data requirements, Engineers to implement reliable pipelines, and Clinical teams to validate data quality and clinical utility.
• Act as a critical liaison to identify and remove operational and technical bottlenecks, ensuring a predictable, scalable, and reliable clinical data flow across all customer markets.

Requirements

• 2+ years of hands-on data analytics experience, with direct exposure to healthcare data interoperability.
• Strong hands-on experience with healthcare data standards: HL7, CCDA, and ADT messages.
• Proficiency in SQL and comfort working with large, complex datasets (claims, clinical logs, interoperability data).
• Background in analyzing interoperability networks (e.g., Carequality, CommonWell, eHealthExchange) or HIE integrations.
• Skilled at data visualization and able to present complex findings to both technical and non-technical stakeholders.
• Strong investigative mindset, i.e., you enjoy digging into the "why" behind missing data and diverging metrics.
• Self-directed and able to manage multiple analytical projects (vend