The Work
You will help train AI systems by creating realistic data science problems and judging how well AI-generated answers handle them. Your feedback should reflect the accuracy, usefulness, and feasibility expected in professional or research settings.
- Create problems and scenarios involving modeling, analysis, experimentation, and feature engineering.
- Evaluate AI-generated responses for technical accuracy and practical feasibility.
- Judge whether responses match real data science work in professional or research settings.
- Write structured feedback that helps improve AI model performance.
- Work independently on project tasks in a remote, asynchronous environment.
What It Pays and Takes
This is ongoing, part-time project work designed to fit alongside a current role. The work has no set schedule, and you must be able to complete at least 20 hours per week.
- $120 per hour.
- Open to candidates residing in the United States.
- Fluent in English.
- At least one year of professional or research experience with hands-on data science work.
- A bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or a related field.
- Strong knowledge of machine learning and applied ML, statistical modeling and experimentation, or large-scale data analysis and feature engineering.
- Strong written communication, close attention to detail, and the ability to explain complex data science ideas clearly.
- Ability to work independently in a remote, asynchronous environment.
- Experience at a recognized technology company may strengthen your background.
- Experience with A/B testing, causal inference, model development, statistical analysis, or production-scale feature engineering is especially relevant.