Responsibilities
- Build next-generation fraud detection capabilities by researching and prototyping state-of-the-art methods across graph ML, sequential modeling, and multimodal learning.
- Owning a research roadmap that ships: moving from papers/prototypes to measurable product impact.
- Publishing applied research and collaborating with a high-caliber team across Data, Product, and Engineering.
- Working with one of the largest financial datasets to generate insights that help hundreds of millions of consumers achieve greater financial freedom.
Qualifications
- PhD strongly preferred; we will consider equivalent research experience with a strong publication/innovation track record.
- 3+ years of experience as a Machine Learning Engineer or Research Scientist.
- Strong scientific rigor and communication.
- Strong Python skills + ability to build high-quality research prototypes.
- Fraud / security / abuse domain experience is a plus.
- Experience with large-scale training, graph systems, and sequential modeling expertise is a plus.
