The opportunity
The Credit Risk team develops intelligent systems that help Stripe identify high-risk accounts, minimize credit losses, and improve profitability. Credit risk is a complex machine learning problem that requires us to distinguish emerging risk from healthy business activity while…
What you'll do
Set and execute the strategy for detecting and mitigating credit risk through machine learning
Own outcomes related to credit losses, profitability, detection quality, and the user experience
Lead the design and delivery of reliable machine learning models, services, and decision systems
Translate advances in machine learning into practical capabilities that support the team’s business goals
Partner with Product, Data Science, Credit Strategy, Operations, and: engineering teams to define priorities and deliver cross-functional programs
Recruit, hire, and develop machine learning engineers while building an inclusive and effective team
What they're looking for
- + years of experience managing engineers who build and operate production machine learning systems
- Experience applying machine learning to complex, real-world problems and: leading the technical delivery of models and supporting systems
- Experience setting strategy and working across engineering, product, data: science, operations, and business teams to deliver measurable outcomes
- Experience recruiting, managing, and developing engineers in a fast-moving: environment with significant autonomy
- Experience with credit risk, fraud detection, financial risk, trust and: safety, or another domain involving decisions under uncertainty
- Experience balancing risk reduction with customer or user experience
- Experience building machine learning systems that support high-stakes, time-sensitive decisions at scale
- Experience setting a multi-year technical direction while delivering progress through quarterly plans