Quantitative Finance Specialist

Research contribution

Researchers will evaluate AI-generated content using deep knowledge of mathematical finance, risk modeling and quantitative research. The aim is to help models handle the subject with greater accuracy and a better understanding of research methodology.

• Create expert training data grounded in finance research
• review AI responses for accuracy and relevance
• provide feedback on the methods and reasoning used.

Relevant academic experience

A master's degree or PhD in Quantitative Finance, Mathematical Finance or Financial Engineering is required. Relevant research or coursework includes computational or mathematical finance, portfolio or risk management, statistical finance, trading and market microstructure.

Familiarity with arXiv's Quantitative Finance repository, q-fin, is required. Clear writing, close attention to detail and independent asynchronous work with AI research teams are important.

Prior experience contributing to AI projects is not needed. The central contribution is subject knowledge and the ability to judge the quality and relevance of AI-generated work.

Pay and working pattern

Rates reach up to $50 per hour, depending on the project. This is ongoing, part-time contract participation rather than a conventional academic or full-time position, and can sit alongside research, teaching, postdoctoral work or employment.

The work is entirely remote with flexible, asynchronous scheduling. No minimum number of weekly hours applies; contributors on active projects commonly work around 5–20 hours a week.

Matching depends on current research needs and available projects. Contributors may be considered for future assignments as new work becomes available. Registration, identity verification and relevant project onboarding precede the start of paid work.