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StripeStripeUnited States

Credit Risk Strategy and Analytics

Drive credit risk strategy for Stripe Capital by architecting policies, analyzing data (proprietary + third-party), monitoring portfolios, and collaborating with Product, Data Science, and Engineering teams to underwrite and scale lending products.

Salary not listed
Remote5+ YOEData Analytics

About the role

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

SQLExcelGoogle SheetsPythonRStataCredit Scoring Models

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