The work
You will create expert-level training data and assess AI-generated responses about quantitative finance. Your feedback will help improve how AI systems understand and explain financial research.
The work is remote, flexible, and asynchronous. You will work independently and use careful judgment when reviewing technical content.
- Create training data based on quantitative finance research and academic knowledge.
- Evaluate AI responses for accuracy, relevance, and alignment with quantitative finance methods.
- Review topics such as computational finance, portfolio management, risk management, statistical finance, trading, and market microstructure.
- Write clear feedback that helps improve AI understanding of quantitative finance research.
What it pays and takes
- Pay: $150 per hour.
- Schedule: 20 or more hours per week; the work is flexible and asynchronous.
- Location: Open to candidates in the United States; the role is remote.
- Education: A master's or doctoral degree in quantitative finance, mathematical finance, or financial engineering.
- Skills: Strong written communication, research ability, technical accuracy review, independent work, and careful attention to detail.
- Research background: Familiarity with arxiv.org, especially its Quantitative Finance repository, q-fin.
- Helpful experience includes computational or mathematical finance, portfolio management, risk management, statistical finance, trading, or market microstructure.
- No prior AI experience is required.
How it works
Apply on OpenTrain with your resume, then complete the application on the hiring site.