Engineering Manager, Machine Learning - Credit Risk
About this role
Analytical leaders who enjoy balancing risk mitigation with user experience will thrive in this engineering management position. The Credit Risk team builds intelligent systems to identify high-risk accounts, minimize credit losses, and improve overall profitability for Stripe.
Day-to-day responsibilities involve setting technical and product direction, connecting machine learning advances to business outcomes, and collaborating closely with product, data science, credit strategy, and operations partners. The role exists to scale credit risk management and guide engineers in delivering reliable systems that protect revenue without hindering legitimate users.
What you will do
- Set and execute the strategic vision for detecting and mitigating credit risk using machine learning.
- Take ownership of outcomes related to credit losses, profitability, detection quality, and user experience.
- Lead the design and delivery of reliable machine learning models, services, and decision systems.
- Translate recent advances in machine learning into practical capabilities supporting core 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 fostering an inclusive and effective team culture.
- Contribute to broader engineering and machine learning initiatives as an active member of the company's management team.
What you need
- Bring at least 3 years of experience managing engineers who build and operate production machine learning systems.
- Demonstrate hands-on experience applying machine learning to complex, real-world problems and leading technical delivery.
- Show proven ability to set strategy and collaborate across engineering, product, data science, operations, and business teams.
- Have a track record of recruiting, managing, and developing engineers in a fast-moving environment with significant autonomy.
Nice to have
- 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
- Experience managing geographically distributed teams
Skills and tech stack
Questions candidates ask
What does the Credit Risk team actually do?
The Credit Risk team develops intelligent systems that help Stripe identify high-risk accounts, minimize credit losses, and improve profitability. They build models and systems used across Stripe's credit-risk products to distinguish emerging risk from healthy business activity.
Who will I work with in this role?
You will work closely with partners in Product, Data Science, Credit Strategy, Operations, and other engineering teams. Together, you help stakeholders make informed decisions and support sustainable growth wherever credit risk affects Stripe's products.
What are the core expectations for the engineering manager?
You will set the team's technical and product direction, connect advances in machine learning to measurable business outcomes, and help engineers deliver reliable systems. Additionally, you will hire and develop engineers and strengthen the team's technical practices.