The work
You will create expert-level training data and review AI-generated content about quantitative finance. Your feedback will help assess whether responses are accurate, relevant, and consistent with accepted research methods.
The work is project-based and ongoing, with contributions made independently during active project periods.
- Create training data based on quantitative finance research and academic knowledge.
- Evaluate AI responses for accuracy, relevance, and correct treatment of quantitative finance concepts.
- Give clear feedback based on quantitative reasoning, research methods, and field standards.
- Work independently and asynchronously with AI research teams.
What it pays and takes
This is a fully remote, part-time contractor opportunity for candidates in the United States. The work uses a flexible, asynchronous schedule.
- Pay: up to $50 per hour.
- Time: 20 or more hours per week.
- Location: open to candidates in the United States.
- Language: professional fluency in English.
- Education: a master's or PhD in quantitative finance, mathematical finance, or financial engineering.
- Experience or coursework in computational finance, mathematical finance, portfolio management, risk management, statistical finance, trading, or market microstructure.
- Familiarity with arXiv, especially its Quantitative Finance repository, q-fin.
- Strong written communication, close attention to detail, and the ability to work independently.
- Experience with quantitative finance research, risk modeling, or quantitative methods is helpful.
- Prior AI experience is not required.