Data Analyst, Clinical Data Effectiveness

🕒 July 27

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📉 Data Analyst

👻 Ghost score 56%

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Counterpart Health

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2024

🏥 Healthcare

🤖 Artificial Intelligence

☁️ SaaS

Healthcare • Artificial Intelligence • SaaS

Counterpart Health is an AI-powered physician enablement platform that delivers data-driven, point-of-care insights to support value-based care. Incubated at Clover Health as Clover Assistant, its proprietary machine-learning models ingest data from 100+ sources, integrate with EHRs, and surface prioritized clinical actions to improve post‑hospitalization follow-up, quality (HEDIS) performance, and cost/risk management for payors, ACOs, and primary care practices. The company offers web-based SaaS integrations, flexible partnership models for value‑based care transformation, and patented ML technologies for diagnosis and medication management.

📋 Description

• Serve as the Subject Matter Expert for clinical data completeness and effectiveness • Own the end-to-end understanding of the clinical data lifecycle, including data sources, breakdowns, and vendor or integration pathway performance • Identify and monitor healthcare facilities generating high-quality, usable clinical documents • Map and correlate facility-specific data across claims, CCDAs, and ADT messages to uncover missingness, latency, or incongruence • Establish transparent reporting on ADT coverage across geographic, organizational, and technological dimensions • Recommend and guide optimal technical configurations for existing data vendors • Evaluate and conduct proof-of-concepts for new data integration technologies • Determine the existence and completeness of documentation for patient visits or encounters • Develop a framework for prioritizing facility targets for direct data acquisition • Guide vendor strategy for TEFCA and QHIN adoption • Partner with Product Managers, Engineers, and Clinical teams to define requirements, implement pipelines, and validate data quality • Identify and remove operational and technical bottlenecks to ensure predictable, scalable, reliable clinical data flow

🎯 Requirements

• 5+ 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 presenting complex findings to technical and non-technical stakeholders • Strong investigative mindset • Self-directed and able to manage multiple analytical projects without constant supervision • Experience with TEFCA/QHIN frameworks and evolving national interoperability standards (preferred) • Familiarity with Bamboo Health, HSX, Particle Health, or Kno2 (preferred) • Background in value-based care, population health, or clinical data operations (preferred) • Experience with claims-clinical data reconciliation (preferred) • Comfort working with Python or similar tools for data manipulation and automation (preferred)

🏖️ Benefits

• Competitive base salary • Equity opportunities • Performance-based bonus program • 401(k) matching • Regular compensation reviews • Comprehensive medical coverage • Dental coverage • Vision coverage • No-Meeting Fridays • Monthly company holidays • Access to mental health resources • Generous flexible time-off policy • Remote-first culture supporting collaboration and flexibility • Learning programs • Mentorship • Professional development funding • Regular performance feedback and reviews • Employee Stock Purchase Plan (ESPP) offering discounted equity opportunities • Reimbursement for office setup expenses • Monthly cell phone & internet stipend • Collaboration with global teams • Paid parental leave for all new parents

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