Credit Risk Strategy and Analytics

What you’ll do

As a key member of the Capital team, you will have the opportunity to shape the future of Stripe's credit policy by driving meaningful changes to the risk and underwriting framework. You will leverage Stripe's vast data assets to formulate your recommendations and work closely with our partners and, where applicable, leverage third-party data. We are a small and lean team, which means you will have the autonomy and the responsibility to manage end-to-end risk initiatives.

Responsibilities

• Architect and implement credit policies based on Stripe's proprietary data and selected industry data to target, price, and size capital products.

• Utilize your analytical and technical skills to provide credit risk recommendations, deliver insights, and support strategic business decisions.

• Collaborate with cross-functional teams, such as Product, Data Science, Engineering, and Capital Markets to shape new product development across different geographies and industries.

• Incorporate third-party data, including bureau, bank account, financial statements, and less traditional data, into our credit assessment.

• Analyze account activity and monitor portfolio trends to identify opportunities for Stripe to reduce potential credit losses.

• Help scale risk processes by working with partners to design and optimize outsourced workflows.

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 experience in credit analysis and underwriting.

• Bachelor's degree in finance, economics, statistics, or a related field.

• Experience in risk management, financial lending, or core credit risk management function.

• Strong analytical skills and a rigorous, data-driven approach to problem-solving.

• Experience working with both internal and external stakeholders and the ability to closely. manage expectations and deliverables in a timely manner.

• Ability to thrive in an unstructured and fast-moving organization.

• Strong technical expertise, including SQL, excel, google sheets.

• Self-starter who can work independently.

Preferred qualifications

• Experience with quantitative tools such as Python, R, or Stata.

• Master's degree in finance, economics, statistics, or a related field.

• Superior communication and relationship management skills.

• Experience with credit scoring models.

• Experience working with machine learning teams.

• Ability to communicate results clearly with a focus on driving impact.