Health Policy & Management

About the Role

Alignerr partners with leading AI research teams and labs to build and train cutting-edge AI models. Seeking Masters in Public Health (MPH) graduates to train AI models for accurate, evidence-based health information and policy analysis. This role involves challenging Large Language Models on their understanding of population health, biostatistics, and global health equity, ensuring prioritization of scientific consensus and ethical health guidelines.

Key Responsibilities

• 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. 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 & Tech Stack

• 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: 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.

Compensation & Logistics

• Compensation: $35–$55 /hour
• Location: Remote
• Commitment: 10–40 hours/week
• Fully remote with flexible weekly hours.
• 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.