You will help improve AI systems by creating difficult quantitative problems and reviewing the answers they produce. Your feedback should show whether an answer is accurate, practical, and consistent with how working quants approach research, trading, risk, and portfolio decisions.
The work is remote and asynchronous. You will complete project tasks independently and use your judgment across quantitative research, alpha or signal generation, trading strategy design and execution, risk modeling, and portfolio construction.
- Create expert-level quantitative problems and realistic scenarios.
- Review AI-generated quantitative responses for accuracy and practical feasibility.
- Assess whether responses match methods used by practicing quants.
- Write structured feedback to help improve AI model performance.
What it pays and takes
This is a flexible, project-based contractor role for candidates in the United States. The role is listed as entry level, while the work requires hands-on quantitative experience and a relevant degree.
- Pay: Up to $150 per hour.
- Hours: 20+ hours per week.
- Schedule: Flexible, remote, and asynchronous, with no set schedule.
- Location: Open to candidates in the United States.
- Language: Fluent English.
- Experience: At least one year of professional, hands-on experience as a quant at a top company or fund.
- Education: Bachelor's degree in mathematics, statistics, computer science, or a related quantitative field.
- Expertise: Quant research and alpha or signal generation, trading strategy design and execution, or risk modeling and portfolio construction.
- Skills: Strong written communication, close attention to detail, and the ability to explain complex quantitative ideas clearly.
- Helpful background: Experience at a recognized quantitative fund or trading firm, plus practical experience with research, modeling, strategy development, and evaluating technical reasoning.
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 better artificial intelligence, including writing examples, rating model responses, and explaining what makes an answer accurate or useful. People with specialist knowledge are paid to apply their professional judgment so models can handle realistic technical problems.