Hospital Health Data Governance Lead

Alignerr; Austin (CO); Remote; USD 55,000 - 138,000; Part time

Job summary

Alignerr is seeking a Hospital Health Data Governance Lead (AI Training) for a remote hourly contract. You will evaluate AI outputs against hospital data governance standards and HIPAA compliance, identify gaps, and provide structured feedback to improve data quality and clinical soundness.

The role is fully remote, flexible, and suited for seasoned health data professionals who can work asynchronously. 10–40 hours/week with potential for ongoing engagements.

Qualifications

• Experience in healthcare data governance and clinical data management.
• Strong knowledge of HIPAA and privacy regulations.
• Clear, structured written communication with ability to summarize complex findings.

Responsibilities

• Evaluate AI-generated outputs related to hospital data governance frameworks and data quality.
• Assess compliance and clinical soundness of AI outputs under HIPAA and standards.
• Identify gaps, errors, or unsafe assumptions in AI-generated content.
• Provide structured feedback to improve AI systems' understanding of hospital data workflows.
• Review data integrity, security, interoperability, and policy enforcement in scenarios.
• Work independently and asynchronously on your own schedule.

Skills

Healthcare data governance

Clinical data management

HIPAA compliance

Technical writing

Stakeholder communication

Job description

Hospital Health Data Governance Lead (AI Training)

About The Role

What if your expertise in healthcare data governance could directly shape how AI understands, interprets, and works with clinical and operational health data? We're looking for experienced Hospital Health Data Governance Leads to help train and evaluate cutting-edge AI models — ensuring they accurately reflect the standards, frameworks, and complexities of real-world hospital data environments.

This is a fully remote, flexible contract role built for seasoned health data professionals. Your domain knowledge is the asset — no prior AI experience required.

• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote
• Commitment: 10–40 hours/week

What You'll Do

• Evaluate AI-generated outputs related to hospital data governance frameworks, clinical data quality, and healthcare compliance
• Apply your expertise in HIPAA and other regulatory standards to assess whether AI responses are accurate, compliant, and clinically sound
• Identify gaps, errors, or unsafe assumptions in AI-generated healthcare data governance content
• Provide structured, detailed feedback that helps AI systems better understand cross-functional hospital data workflows
• Review scenarios involving clinical data integrity, data security, interoperability, and policy enforcement
• Work independently and asynchronously — fully on your own schedule

Who You Are

• Experienced in healthcare data governance, clinical data management, or health information operations
• Strong working knowledge of healthcare privacy laws and regulatory frameworks, including HIPAA
• Comfortable navigating the intersection of clinical, IT, compliance, and administrative stakeholders
• Methodical and detail-oriented — you spot inconsistencies and know what good governance looks like in practice
• Clear, structured written communicator who can articulate complex findings concisely
• No prior AI or machine learning experience required

Nice to Have

• Prior experience with data annotation, data quality assurance, or evaluation workflows
• Familiarity with EHR systems, health data standards (HL7, FHIR), or clinical informatics
• Background in hospital administration, health IT, or clinical operations
• Experience with data stewardship programs or enterprise data governance initiatives

Why Join Us

• Work at the cutting edge of healthcare AI alongside leading research labs
• Fully remote and flexible — work when and where it suits you
• Freelance autonomy with the structure of meaningful, task-based work
• Make a direct impact on how AI understands and handles sensitive health data
• Contribute to AI development that has real consequences for patient safety and clinical decision-making
• Potential for ongoing work and contract extension as new projects launch