Quantitative Finance AI Research Evaluator

The work

You will create expert-level training data and review AI-generated responses about quantitative finance. Your feedback will help improve how AI systems understand and explain technical financial research.

The work is remote, flexible, and asynchronous. You will work independently while applying careful judgment to technical content.

• Create training data based on quantitative finance research and academic knowledge.
• Check 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 explains how responses can better reflect quantitative finance research.

What it pays and takes

• Pay: $150 per hour.
• Location: Open to candidates in the United States.
• Language: Professional fluency in English.
• Time: 20 or more hours per week.
• Education: A PhD or master's degree 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, technical accuracy review, independent work, and careful attention to detail.
• Helpful background: Coursework or research in 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.

About AI training work

AI training is the human work behind systems that generate and evaluate text. Contributors create examples and review model responses, while subject-matter experts help teach AI to handle specialized topics accurately. OpenTrain helps people find these projects, build a profile, and apply in minutes.