Join Us
RiskLab AI brings together researchers, students and practitioners to build transparent, reproducible tools for financial machine learning. There are several ways to get involved.
Students & researchers
Work alongside faculty and graduate researchers on financial machine learning, causal factor investing and quantitative methods. Ideal for students in finance, statistics, computer science and applied mathematics who want research experience that reaches real practice.
Open-source contributors
Our Python and Julia libraries are public and welcome contributions — from new methods and notebooks to performance work, tests and documentation. Contributing is the fastest way to get involved and be credited in the project.
Industry collaborators
We partner with practitioners to bridge the gap between academic research and applied quantitative finance. If your team is working on problems where our methods could help, we would like to hear from you.
Get in touch
Tell us a little about your background and what you would like to work on. Contributions to the libraries are welcome any time through GitHub.