The work
Create training examples based on quantitative finance research and assess AI-generated answers for accuracy, relevance, and sound methods. You will provide clear written feedback to help improve how AI systems handle quantitative finance research.
- Review work across computational and mathematical finance, portfolio and risk management, statistical finance, trading, and market microstructure.
- Use familiarity with academic research, including arXiv's quantitative finance repository, q-fin.
- Work independently and asynchronously, with careful attention to detail.
What it pays and takes
- Pay: Up to $150 per hour.
- Hours: Flexible schedule; contributors commonly work about 5–20 hours per week when a project is active.
- Location: Remote; open to candidates in the United States.
- Language: Fluent English.
- Education: A PhD or master's degree in quantitative finance, mathematical finance, or financial engineering is required.
- Requirements: Strong research and written communication skills, familiarity with arXiv's q-fin repository, and the ability to assess technical content for accuracy and relevance.
- Helpful background: Coursework or research in computational or mathematical finance, portfolio or risk management, statistical finance, trading, or market microstructure.
- No prior AI experience is required.
How it works
OpenTrain is where you find this role and start your application. Apply on OpenTrain with your resume, then complete the application on the hiring site.