Remote Population Health AI Quality Reviewer

Alignerr Corp.; Austin (CO); Remote; USD 69.000 - 96.000; Vollzeit

Zusammenfassung

Alignerr is seeking a Population Health Informaticist for AI training to help ensure health data, analytics, and public health reasoning are accurately represented in next‑generation AI systems. This remote, hourly contract role offers flexible scheduling and collaboration with leading AI teams.

You will evaluate AI‑generated health content, review data analysis scenarios, and provide expert feedback to improve accuracy and real‑world applicability.

Qualifikationen

• Experience with healthcare datasets and population health data.
• Strong analytical background with data visualization and reporting skills.
• Ability to translate complex health data concepts into clear, actionable insights.

Aufgaben

• Evaluate and improve AI-generated content related to population health and health informatics.
• Review data analysis scenarios, health metrics, and public health strategies for accuracy.
• Identify gaps or oversimplifications in AI outputs related to health disparities and surveillance.
• Provide structured feedback to help AI systems reason more accurately about population health.
• Contribute to design and evaluation of dashboards, data pipelines, and reporting frameworks used in AI training.
• Work independently and asynchronously on task-based assignments.

Kenntnisse

Healthcare data experience

Data visualization

Data interpretation

Analytical thinking

Detail-oriented

Ausbildung

Biostatistics

Health informatics

Public health policy

Jobbeschreibung

Alignerr is seeking a Population Health Informaticist for AI training to help ensure health data, analytics, and public health reasoning are accurately represented in next‑generation AI systems. This remote, hourly contract role offers flexible scheduling and collaboration with leading AI teams.

You will evaluate AI‑generated health content, review data analysis scenarios, and provide expert feedback to improve accuracy and real‑world applicability.