The company is an early-stage RegTech startup focused on KYB/KYC and fraud prevention. They are looking to transform compliance and fraud detection through innovative data-driven solutions and need to build data infrastructure, labeling pipelines, and analytics capabilities from the ground up.
Requirements
- 5+ years of experience in data science, data engineering, or a dual role
- Strong experience in RegTech, financial crime, fraud detection, or compliance systems.
- Prior experience at a KYC/KYB provider, AML team, or financial institution is highly desirable (e.g., fraud teams at fintechs like PayPal).
Responsibilities
- Build and maintain data infrastructure and labeling pipelines.
- Develop models and analytics for fraud prevention and KYB/KYC processes.
- Own projects end-to-end: design, implement, test, and iterate solutions.
- Translate complex business problems into actionable data-driven solutions.
Other
- Hands-on builder who thrives in a fast-moving startup environment.
- Comfortable working across international time zones.
- Side projects, personal builds, or contributions to the data community are a strong indicator of fit.
- Collaborate closely with a small IT team (currently 5 members) and advisors.
