Health Policy & Management - AI Content Specialist

About the role

Your public health expertise is needed where it matters most: ensuring AI gets health right. At Alignerr, we partner with the world's leading AI research labs to build smarter, safer AI models — and we need credentialed public health professionals to make it happen. As a Health Policy & Management AI Content Specialist, you'll directly shape how cutting-edge AI systems understand population health, epidemiology, biostatistics, and health policy. This is a rare opportunity to apply your graduate-level training to a high-impact, fully remote contract role — on your own schedule.

What You'll Do

• Create advanced case studies involving disease outbreak simulations, health equity assessments, and statistical interpretation of clinical trials to challenge and test AI reasoning.
• Write rigorous, step-by-step responses that synthesize peer-reviewed research, epidemiological data, and current guidelines from bodies like the CDC and WHO.
• Evaluate AI-generated health advice and policy recommendations for accuracy, bias, and adherence to ethical standards. Identify misinformation, logical gaps, and reasoning errors.
• Provide structured feedback that helps AI models distinguish correlation from causation, interpret health data correctly, and communicate health risks clearly across diverse populations.

Who You Are

• Holds a Masters in Public Health (MPH), Master of Science in Public Health (MSPH), or a closely related graduate degree.
• Strong foundational knowledge in at least two of: Epidemiology, Biostatistics, Environmental Health, or Health Policy.
• Able to translate complex health data into clear, accurate, and culturally sensitive written communication.
• High attention to detail when evaluating statistical significance, data citations, and the logic of health interventions.
• Self-motivated and comfortable working independently on an asynchronous, task-based schedule.
• No prior AI experience required.

Nice to Have

• Experience with data annotation, data quality review, or evaluation systems.
• Proficiency in data analysis software such as R, SAS, or Stata.
• Background in health communication, clinical research coordination, or public health monitoring.