AI training & evaluation
Quantitative Finance Researcher (Master's)
Handshake AI
You'll draw on your deep expertise in mathematical finance, risk modeling, and quantitative methods to evaluate AI-generated content and provide feedback that helps AI better understand quantitative finance…
- Work arrangement & location
- Remote
Track this job
- Engagement
- Degree filters: Bachelor's, Master's
- Hours
- 5–20 hours per week
Employer description and requirements
Overview
Handshake is looking for quantitative finance academics to support AI research through flexible, hourly contract work. This is not a traditional job. You'll draw on your deep expertise in mathematical finance, risk modeling, and quantitative methods to evaluate AI-generated content and provide feedback that helps AI better understand quantitative finance research and methodology.
This is an ongoing, project-based opportunity you can take on alongside anything else you have going on.
Details
- This project involves using your research expertise and academic knowledge to create expert-level training data and evaluate AI-generated responses for accuracy and relevance. No prior AI experience required.
- Fully remote with a flexible, asynchronous schedule and no minimum hour requirement; most contributors work approximately 5–20 hours per week when participating in an active project.
- Placement depends on current project needs, with opportunities to be considered for future projects as they become available.
Qualifications
- Familiarity with arxiv.org, particularly the Quantitative Finance repository (q-fin)
- PhD or Master in Quantitative Finance, Mathematical Finance, Financial Engineering
- Research background or coursework in areas such as:
- Computational Finance or Mathematical Finance
- Portfolio Management or Risk Management
- Statistical Finance or Trading and Market Microstructure
- Strong written communication skills, attention to detail, and the ability to work independently and asynchronously with AI research teams.