Data Analyst, Clinical Data Effectiveness

Role overview

This position is being handled on behalf of a partner employer, which will manage the application review and the remaining hiring steps. The role is based in the United States and is central to a healthcare AI and clinical data platform that depends on accurate, complete, and usable clinical information to deliver point-of-care insights for physicians.

As the clinical data effectiveness analyst, you will serve as the go-to expert for understanding how healthcare data moves through interoperability networks, EHR systems, and national exchange frameworks. Your work will help reveal where records are missing, delayed, or fragmented across a complex healthcare ecosystem, directly supporting care teams in closing care gaps, managing chronic conditions, and improving value-based outcomes. This is a hands-on analytical role with significant ownership over data quality across multiple vendors and integration paths, and it involves close collaboration with product, engineering, and clinical teams in a fast-moving, mission-focused environment.

Key responsibilities

• Take ownership of end-to-end analysis of clinical data completeness and effectiveness across multiple interoperability channels, surfacing gaps, failures, and inconsistencies in data movement.
• Examine structured and unstructured healthcare sources such as HL7, CCDA, ADT, claims, and clinical summaries to identify records that are missing, delayed, or improperly aligned.
• Create and sustain reporting systems that track data coverage across facilities, regions, vendors, and EMR environments.
• Review existing integration routes with vendors and interoperability networks, then suggest improvements that strengthen data reliability and quality.
• Run comparative evaluations and proof-of-concept reviews for emerging data exchange tools and vendors to inform strategic choices.
• Develop and keep current frameworks that measure the completeness of clinical documentation at the patient encounter level.
• Work with Product, Engineering, and Clinical partners to turn analytical findings into practical changes in data pipelines and platform performance.
• Contribute to initiatives aligned with national interoperability standards, including TEFCA/QHIN, and help ensure compatibility with the evolving healthcare exchange landscape.
• Serve as a key contact for uncovering and resolving operational and technical issues that affect the movement and usefulness of clinical data.

Required qualifications

• At least 2 years of practical experience in data analytics within healthcare or clinical data settings.
• Strong working knowledge of healthcare interoperability standards, especially HL7, CCDA, and ADT messaging.
• Solid SQL skills and experience handling large, complex datasets such as claims, clinical records, or interoperability logs.
• Familiarity with healthcare data exchange networks such as Carequality, CommonWell, or eHealthExchange.
• A sharp analytical approach with the ability to trace root causes behind data gaps and inconsistencies.
• Experience using data visualization tools and presenting findings to both technical and non-technical audiences.
• Ability to independently manage several analytical workstreams with strong organizational discipline.
• Exposure to TEFCA/QHIN frameworks, vendor platforms such as Bamboo Health, HSX, Particle Health, or Kno2, or value-based care settings is an advantage.
• Comfort using Python or similar tools for data manipulation and automation is preferred.

Benefits and compensation

• Base salary range of USD 77,000 to USD 100,000.
• Performance bonus and equity opportunities.
• Medical, dental, and vision coverage.
• 401(k) retirement savings plan with employer support.
• Remote-first work setup with flexibility.
• Generous paid time off and a flexible vacation policy.
• Mental health support and wellness initiatives, including flexible scheduling.
• Professional development, mentorship, and learning support.
• Employee stock purchase plan and additional financial wellness support.
• Monthly stipends for home office setup, phone, and internet costs.
• Paid parental leave and family support benefits.
• Opportunity to contribute to high-impact healthcare AI systems that improve patient outcomes at scale.

Application and privacy notice

The hiring process uses an AI-assisted matching approach to help identify candidates whose profiles best fit the core requirements. Applications are reviewed objectively and the strongest matches are forwarded to the hiring company, which manages interviews, assessments, and final decisions internally.

By applying, you consent to the processing of your personal data for candidate evaluation and sharing relevant details with the employer, in line with applicable data protection laws such as GDPR. You may request access, correction, deletion, or objection regarding your data at any time.

Some parts of the recruitment process may use AI tools to support resume review and response analysis, but human judgment remains part of the final hiring decision. For questions about data handling, you may contact the recruiting team.