Quantitative Finance Researcher (Master's)

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.

How it works

Apply on OpenTrain with your resume, then complete the application on the hiring site.

About AI training work

AI training work is the human side of building artificial intelligence. People create examples and review model responses so AI systems can handle specialized subjects more accurately, which is why experts with strong subject knowledge are needed.