Population Health Informaticist

Job summary

Evaluate and improve AI-generated health analytics, data interpretations, and recommendations for accuracy, clinical relevance, and real-world applicability. Review population health datasets, dashboards, and reporting frameworks, and provide structured feedback on trends, disparities, and intervention strategies.

Job details

Population Health Informaticist (AI Training) About The Role We're partnering with leading AI research teams to build smarter, more accurate health AI — and we need experienced population health informaticists to help make it happen. Your expertise in health data, analytics, and public health strategy will directly shape how AI understands and responds to complex population-level health challenges. This is a fully remote, flexible contract role where your domain knowledge creates real impact. Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week What You'll Do Evaluate and improve AI-generated health analytics, outputs, and data interpretations for accuracy and clinical relevance Review population health datasets, dashboards, and reporting frameworks to identify gaps, errors, or misleading insights Provide structured feedback on AI outputs related to health trends, disparities, and intervention strategies Apply your public health expertise to assess the quality and real-world applicability of AI-generated recommendations Work independently and asynchronously on task-based assignments Who You Are Experienced working with healthcare, public health, or population-level datasets Strong analytical thinker with hands-on knowledge of health data metrics and surveillance systems Skilled at translating complex data into clear, actionable insights Familiar with dashboards, data pipelines, or reporting tools used in public health or health informatics Detail-oriented, reliable, and comfortable working independently Nice to Have Background in epidemiology, biostatistics, or health policy Experience with data annotation, data quality assessment, or evaluation frameworks Familiarity with AI or machine learning applications in healthcare Prior work in community health, health equity, or population surveillance programs Why Join Us Work on cutting-edge AI projects alongside top research labs and health data teams Fully remote and flexible — work on your own schedule Freelance perks: autonomy, variety, and meaningful work Apply your public health expertise to problems that matter at scale Potential for ongoing work and contract extension

What you’ll do

Evaluate and improve AI-generated health analytics, data interpretations, and recommendations for accuracy, clinical relevance, and real-world applicability. Review population health datasets, dashboards, and reporting frameworks, and provide structured feedback on trends, disparities, and intervention strategies.

Requirements

Candidates should have experience with healthcare, public health, or population-level datasets, along with strong analytical skills and practical knowledge of health metrics and surveillance systems. They should be able to translate complex data into actionable insights, work independently, and be familiar with public health dashboards, data pipelines, or reporting tools.

Benefits

• Flexible Schedule
• Remote Work
• Autonomy
• Potential for Ongoing Contract Work

Listed skills

• Health · Preferred
• Reporting · Preferred
• Data analysis · Preferred
• Accuracy · Preferred
• Flexible · Preferred
• Analytical · Preferred
• Teams · Preferred
• assessment · Preferred
• Detail-oriented · Preferred
• Machine learning · Preferred
• Organization · Preferred
• Reliable · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Population Health Informatics
• Health Data Analytics
• Public Health Strategy
• Population Health Datasets
• Health Data Metrics
• Surveillance Systems
• Data Interpretation
• Dashboard Evaluation
• Data Quality Assessment
• Health Reporting
• Epidemiology
• Biostatistics
• Health Policy
• Data Annotation
• Health Equity
• AI Output Evaluation

Job areas

• Healthcare
• Data & Analytics
• Technology
• Science & Research

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