Remote Population Health Informaticist for AI Training

Alignerr Corp.; Indianapolis (IN); Remote; USD 55,000 - 124,000; Part time

Benefits offered by this job

Autonomy

Flexible schedule

Global collaboration

Job summary

Alignerr is seeking a Population Health Informaticist for AI training in a fully remote, flexible hourly contract. You will apply expertise in health data and analytics to evaluate AI systems that interpret population-level health information.

Remote work offers a schedule-driven role with 10–40 hours per week. You will review AI outputs, data pipelines, and health reporting frameworks, providing expert feedback to improve model performance and health insights.

Qualifications

• Experience working with healthcare or population health datasets.
• Strong analytical thinking with ability to identify meaningful patterns.
• Proficiency in data visualization and health reporting dashboards.
• Ability to translate complex health data into actionable insights.
• Detail-oriented and able to work independently on structured tasks.

Responsibilities

• Evaluate AI-generated population health analyses for accuracy and clinical relevance.
• Review data pipelines, dashboards, and reporting frameworks produced by AI systems.
• Identify gaps or mis insights in AI outputs related to health trends and disparities.
• Provide structured feedback to improve AI models’ reasoning about population health.
• Apply domain knowledge of epidemiology/public health to advise on surveillance data and interventions.

Skills

Healthcare data analysis

Public health data

Data visualization

Analytical thinking

Independent work

Tools

Tableau/Power BI

SQL

EHR familiarity

Job description

Alignerr is seeking a Population Health Informaticist for AI training in a fully remote, flexible hourly contract. You will apply expertise in health data and analytics to evaluate AI systems that interpret population-level health information.

Remote work offers a schedule-driven role with 10–40 hours per week. You will review AI outputs, data pipelines, and health reporting frameworks, providing expert feedback to improve model performance and health insights.