Health Policy & Management

Health Policy & Management - AI Data Trainer Location: Remote About The Job At Alignerr, we partner with the world’s leading AI research teams and labs to build and train cutting‑edge AI models. We are seeking Masters in Public Health (MPH) graduates to help train AI models to provide accurate, evidence‑based health information and policy analysis. You will challenge Large Language Models on their understanding of population health, biostatistics, and global health equity—ensuring that the models prioritize scientific consensus and ethical health guidelines. Work on high‑impact projects while earning $35+/hour, fully remote, with flexible weekly hours. Organization: Alignerr Position: Health Policy & Management - AI Data Trainer Type: Hourly Contract Compensation: $35–$55 /hour Location: Remote Commitment: 10–40 hours/week What You’ll Do Develop Complex Problems: Design advanced public health scenarios involving disease outbreak simulations, health equity assessments, and statistical interpretation of clinical trials. Author Ground‑Truth Solutions: Create rigorous, step‑by‑step responses that synthesize peer‑reviewed research, epidemiological data, and current public health guidelines (e.g., CDC, WHO standards). Technical Auditing: Evaluate AI‑generated health advice and policy recommendations for accuracy, bias, and adherence to ethical standards. You will identify "misinformation" or logical gaps in the AI's health reasoning. Refine Reasoning: Provide structured feedback to help the model distinguish between correlation and causation in health data and improve its ability to communicate risks to diverse populations. Requirements Advanced Degree: Masters in Public Health (MPH), Master of Science in Public Health (MSPH), or a closely related graduate degree. Domain Expertise: Strong foundational knowledge in at least two core pillars: Epidemiology, Biostatistics, Environmental Health, or Health Policy. Analytical Writing: The ability to translate complex health data into clear, actionable, and culturally sensitive written information. Attention to Detail: High level of precision when checking statistical significance, data citations, and the logic of health interventions. No AI experience required. Preferred Prior experience with data annotation, data quality, or evaluation systems. Experience with data analysis software such as R, SAS, or Stata. Prior experience in health communication, clinical research coordination, or public health monitoring. Why Join Us Competitive pay and flexible remote work. Direct engagement with industry‑leading LLMs. Contractor advantages: high agency, agility, and international reach. More opportunities for contracting renewals. #J-18808-Ljbffr