Epidemiologist - AI Trainer

Overview

This role is for experienced quantitative specialists who want to help improve AI systems. You will collaborate with advanced models on work such as reviewing AI-produced quantitative analysis, solving technical challenges, and giving feedback that improves how these systems reason through data, models, and scientific questions.

The position is suitable for people from fields like data science, astrophysics, economics, biostatistics, operations research, epidemiology, and other similar quantitative areas. If you are comfortable applying rigorous thinking to data and models, your background may be a strong fit. Some people take on this work alongside another full-time job, while others use it as their main source of work.

After creating an account, you will complete a short assessment that acts as the screening step. If you are successful, you will receive confirmation by email and paid assignments will then be available through the platform.

What You Will Do

You will assess AI-generated quantitative work for correctness and practical validity, create and solve problems that help train and evaluate AI models, produce clear technical explanations, and write or review analytical code with strong documentation. Your input will directly influence the next generation of AI systems designed for quantitative reasoning.

Contract Benefits

You can choose the projects you want to take on and decide when you work. The role is flexible, letting you work on your own schedule using your own computer from home.

Compensation is paid hourly, starting at USD 50 to USD 100+ per hour, with bonus pay available on some assignments.

Requirements

Applicants should have at least 2 years of practical experience in a quantitative role or research setting, such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or a related area. You should also have some coding experience and be comfortable writing and reviewing analytical code from start to finish.

Experience with statistical techniques, predictive modeling, and experimental design is important, including areas such as A/B testing, hypothesis testing, regression, classification, and time-series forecasting. Strong written English at a native or bilingual level is required.

A bachelor's degree in a quantitative discipline such as Statistics, Computer Science, Mathematics, or Engineering is preferred, and a master's degree or PhD is an advantage. Additional credentials, such as a strong Kaggle ranking or AWS/GCP machine learning certifications, are also beneficial.

Additional Information

This is an independent contractor engagement. Payment is processed through PayPal, and currency conversion from USD will be handled by PayPal. You will never be asked to pay any money to participate. Only candidates based in the United States, Canada, the United Kingdom, Ireland, Australia, and New Zealand will be considered.

Tags

#datascience