Remote Health Informatics Analyst - AI Quality Evaluator

Alignerr Corp.; United States; Remote; USD 34,000 - 83,000; Part time

Benefits offered by this job

Autonomy

Variety

Global collaboration

Job summary

Alignerr Corp. is seeking a Health Informatics Analyst (AI Training) to help evaluate and improve AI systems trained on healthcare data. You will apply your clinical data expertise to shape how AI understands and communicates health information.

Remote hourly contract: 10–40 hours/week. You will analyze AI outputs, review clinical terminology, and provide structured feedback to ensure real-world applicability. Ideal candidates have hands-on healthcare data experience and strong analytical skills.

Qualifications

• Hands-on experience with healthcare data, EHR systems, or clinical reporting platforms.
• Strong analytical skills including data interpretation, trend analysis, and reporting.
• Ability to assess information quality across clinical and operational contexts.
• Clear written communication skills.

Responsibilities

• Analyze and evaluate AI-generated healthcare content, clinical workflows, and EHR-related outputs for accuracy and real-world applicability
• Review and assess AI responses involving health data, clinical terminology, and health information systems
• Identify errors, gaps, or unrealistic outputs in AI-generated clinical and operational scenarios
• Provide structured, expert feedback using clear evaluation rubrics
• Support data quality and annotation tasks related to healthcare datasets
• Work independently and asynchronously on your own schedule

Skills

Analytical skills

Data interpretation

Trend analysis

Reporting

Tools

HL7

FHIR

ICD coding

Job description

Alignerr Corp. is seeking a Health Informatics Analyst (AI Training) to help evaluate and improve AI systems trained on healthcare data. You will apply your clinical data expertise to shape how AI understands and communicates health information.

Remote hourly contract: 10–40 hours/week. You will analyze AI outputs, review clinical terminology, and provide structured feedback to ensure real-world applicability. Ideal candidates have hands-on healthcare data experience and strong analytical skills.