The work
You will create training data and assess AI-generated answers about quantitative finance. Your feedback will help improve how AI systems handle technical financial research and methods.
- Create training data based on quantitative finance research and academic knowledge.
- Evaluate AI-generated responses for accuracy, relevance, and sound 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 responses about quantitative finance research.
- Work independently and maintain close attention to detail.
What it pays and takes
This is an ongoing, project-based opportunity that can fit alongside other commitments.
- Pay: $150 per hour.
- Schedule: Flexible and asynchronous, with a 20+ hour weekly requirement.
- Location: Open to candidates in the United States.
- Language: Fluent in English.
- Education: Master's or PhD in quantitative finance, mathematical finance, or financial engineering.
- Research: Familiarity with arxiv.org, especially its Quantitative Finance repository, q-fin.
- Skills: Strong written communication, research ability, and the ability to judge technical content for accuracy and relevance.
- Helpful background: Computational or mathematical finance, portfolio management, risk management, statistical finance, trading, or market microstructure.
How it works
Apply on OpenTrain with your resume and then complete the application on the hiring site.