Hospital Health Data Governance Lead

Alignerr; Charlotte (AR); Remote; USD 55,000 - 124,000; Part time

Benefits offered by this job

Fully remote

Freelance autonomy

Contract extension possible

Job summary

Alignerr Corp. is seeking a Hospital Health Data Governance Lead (AI Training) to ensure accuracy, privacy, and compliance of hospital data used in AI training at scale.

This remote hourly contract role offers flexible 10-40 hours per week and the opportunity to shape data governance practices across clinical and administrative domains. You will evaluate records, identify gaps, draft actionable feedback, and collaborate with cross-functional teams, including clinical, IT, and compliance

Qualifications

• Experience in healthcare data governance or health information operations.
• Strong working knowledge of privacy regulations (HIPAA) and related standards.
• Ability to evaluate data quality across clinical, operational, and administrative domains.

Responsibilities

• Evaluate and validate hospital health records for accuracy, consistency, completeness, and security against governance standards.
• Identify gaps and compliance risks in data structures, workflows, and documentation.
• Assess data policies for safe patient care and informed decision-making across clinical and IT contexts.
• Provide structured, detailed feedback on health data quality, classification, and governance controls.
• Work independently and asynchronously on your own schedule.

Skills

Healthcare data governance

HIPAA knowledge

Data quality assessment

Cross-functional teamwork

Written 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 hospital data at scale? We're looking for experienced health data governance leaders to help ensure that the hospital data used in cutting-edge AI training is accurate, trusted, compliant, and ready for clinical, regulatory, and analytical use.

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

What You'll Do

• Evaluate and validate hospital health records for accuracy, consistency, completeness, and security against established governance standards
• Identify gaps, inconsistencies, and compliance risks in healthcare data structures, workflows, and documentation
• Apply knowledge of clinical, IT, and compliance frameworks to assess whether data policies support safe patient care and informed decision-making
• Review and provide structured, detailed feedback on health data quality, classification, and governance controls
• Work independently and asynchronously - 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 and regulatory frameworks - including HIPAA and related standards
• Able to evaluate data quality across clinical, operational, and administrative domains
• Detail-oriented and systematic - you notice when data doesn't meet the standards it should
• Comfortable working cross-functionally across clinical, technical, and administrative contexts
• Clear and concise written communicator who can document findings effectively

Nice to Have

• Prior experience with data annotation, data quality evaluation, or AI training data workflows
• Background in EHR systems, health information management, or clinical informatics
• Familiarity with data governance frameworks such as DAMA-DMBOK or FAIR data principles
• Experience in hospital compliance, audit, or regulatory reporting environments

Why Join Us

• Work at the intersection of healthcare data and some of the most advanced AI research in the world
• Fully remote and flexible - work when and where it suits you
• Freelance autonomy with the structure of meaningful, high-impact work
• Exposure to large-scale health data systems and real-world AI model training pipelines
• Contribute to AI development that could meaningfully improve how clinical systems understand and use health data
• Potential for ongoing work and contract extension as new projects launch