Health Informatics Analyst
Indexed description
At Alignerr, we partner with the world's leading AI research teams and labs to build and train cutting-edge AI models. This is your opportunity to put your clinical data knowledge to work at the frontier of AI development.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
- Review and evaluate AI-generated healthcare content, clinical workflows, and EHR-related outputs for accuracy and appropriateness
- Analyze healthcare and electronic health record (EHR) data to identify trends, gaps, and areas for improvement
- Assess the quality of AI responses related to clinical decision-making, health system operations, and medical data interpretation
- Provide structured, expert feedback on data pipelines, reporting tools, and health information system outputs
- Flag errors, inconsistencies, or clinically unsafe content in AI-generated materials
- Work independently and asynchronously on your own schedule
- Hands-on experience with healthcare data, EHR systems, or clinical reporting platforms
- Strong analytical skills including data visualization, trend analysis, and structured reporting
- Ability to evaluate clinical and operational content with a critical eye for accuracy
- Comfortable collaborating across clinical, technical, and operational contexts
- Detail-oriented with a commitment to data quality and integrity
- No prior AI experience required — your healthcare expertise is what matters
- Experience with data annotation, data quality assurance, or evaluation frameworks
- Familiarity with health information standards (HL7, FHIR, ICD coding, etc.)
- Background in clinical informatics, health IT, or population health analytics
- Work on cutting-edge AI projects with top research labs and AI teams
- Fully remote and flexible — work on your own schedule, 10–40 hours/week
- Freelance perks: autonomy, variety, and global collaboration
- Contribute to meaningful work that improves how AI serves healthcare professionals and patients
- Exposure to advanced large language models (LLMs) and how they are trained and evaluated
- Potential for ongoing work and contract extension
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