Credit Risk Strategy and Analytics
Drive credit risk strategy for Stripe Capital by architecting policies, analyzing proprietary and third-party data, monitoring portfolio trends, and collaborating with Product, Data Science, and Engineering teams to shape lending products. Requires 5+ years credit analysis experience, strong SQL and data-driven skills.
About the job
Responsibilities
- Architect and implement credit policies based on Stripe's proprietary data and selected industry data to target, price, and size capital products.
- Utilize 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.
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.
Skills
SQL, Excel, Python, R, Stata, Credit Scoring, Machine Learning, Risk Management, Credit Analysis, Underwriting
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