Credit Risk Strategist, Risk Foundations
at Stripe
Chicago, Toronto, United States (Remote), Canada, United States
Who we are
About Stripe
Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.
About the team
Risk Foundations is a small, high-leverage team with a mandate to maximize Stripe’s enterprise value by managing risk across the user lifecycle. Whether we’re evaluating net-new opportunity areas, investigating existential threats, or finding ways to unlock value in the existing business, we approach problems with rigor, nuance, and intellectual humility. If you are excited to shape the infrastructure that powers safe, sustainable growth for millions of businesses, we encourage you to apply!
What you’ll do
Stripe handles billions of dollars every year for businesses around the world, and the Risk team plays a critical role in the company’s financial and partnership success. As a Strategist on the Risk Foundations team, you will help manage a rapidly growing merchant portfolio by guiding Stripe’s credit strategy and devising growth-friendly solutions that reduce overall credit risk. This is a high impact role that involves cross-functional partnership with Data Science, Engineering, Product, and Operations.
Responsibilities
- Develop scalable methods to identify, measure, and control end-to-end risks (including Credit and Fraud) across the user lifecycle: this will involve identifying and shaping crucial risk management systems including in-product and back-end controls, use of external risk assessment tools, and implementation of rule-based and model-based detection systems
- Proactively identify risk management opportunities, outline the strategy and translate complex requirements into technical specifications, which may include shipping code to enable rapid iteration of risk strategy
- Work closely with Product, Engineering, and Data Science teams to shape new product offerings and develop data-driven, globally scalable systems and processes that combine strong risk management fundamentals with seamless user experiences.
- Become an expert on the global ecosystem of Stripe’s products, integrations, tools, and partner requirements, and how those elements interact with payment risks
- Develop strong internal relationships across partner teams (Data Science, Product, Engineering, Treasury, Sales, Operations, and Finance)
- Challenge the payments industry status quo to help enable innovative businesses to flourish online
Who you are
We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.
Minimum requirements
- 5+ years of relevant experience with financial risk modeling
- A builder’s mindset with a willingness to question assumptions and conventional wisdom
- Analytical: You are well versed in data analysis, modeling, and can frame business decisions and tradeoffs effectively through quantitative analysis and visualization
- Collaborative: Ability to work effectively across teams, building strong working relationships in order to successfully execute on shared deliverables
- Decisive, yet open to learning: you will make many critical decisions every day impacting large numbers of merchants. You are willing to make these difficult decisions and quickly learn and iterate from these experiences.
- Understanding and empathetic to the challenges of setting up a new business: You will thoughtfully balance scaled enforcement decisions with user experience.
- An enthusiastic “roll up your sleeves” mentality
- Experience with SQL required
- Bachelor’s degree in Economics, Statistics, Computer Science, Engineering or other quantitative or related field
Preferred qualifications
- Experience with Python
- Demonstrated experience working in fast paced highly ambiguous environments
- Familiarity with LLM agents and how they can augment risk management practices
