Public Health AI Data Trainer - Remote

Alignerr Corp.; Manchester; On-site; GBP 42,000 - 83,000; Part time

Benefits offered by this job

Fully remote

Flexible hours

Global collaboration

Job summary

Alignerr is seeking an MPH-trained AI Data Trainer to help ensure AI provides accurate, evidence-based health information. This fully remote, hourly contract role leverages epidemiology, biostatistics, health equity, and policy expertise to shape AI reasoning about population health.

You will design advanced public health scenarios, author rigorous ground-truth solutions, and audit AI outputs for accuracy and bias, with no prior AI experience required.

Qualifications

• Masters in Public Health or closely related degree.
• Knowledge in at least two areas: Epidemiology, Biostatistics, Environmental Health, or Health Policy.
• Ability to translate health data into clear, actionable content.
• Detail-oriented in evaluating statistics, data citations, and health intervention logic.
• No prior AI experience required.
• Experience with data annotation or evaluation systems is a plus.

Responsibilities

• Design complex public health scenarios and disease outbreak simulations.
• Author grounded-truth solutions based on peer-reviewed research and guidelines.
• Audit AI outputs for accuracy, bias, and ethical standards; identify gaps.
• Refine AI reasoning by clarifying correlation vs. causation and risk communication.

Skills

Epidemiology

Biostatistics

Health Policy

Data interpretation

Education

MPH (Master of Public Health)

MSPH (Master of Science in Public Health)

Tools

R

SAS

Stata

Job description

Alignerr is seeking an MPH-trained AI Data Trainer to help ensure AI provides accurate, evidence-based health information. This fully remote, hourly contract role leverages epidemiology, biostatistics, health equity, and policy expertise to shape AI reasoning about population health.

You will design advanced public health scenarios, author rigorous ground-truth solutions, and audit AI outputs for accuracy and bias, with no prior AI experience required.