Principal Credit Analytics

Upstart · Fintech · Remote · Data Analytics

This role is for a Principal Credit Analytics at Upstart, a fintech company focused on AI-driven lending. The role involves leading credit forecasting, valuation, and risk capital analytics to inform portfolio strategy and funding decisions. It requires strong analytical and technical skills, experience in credit risk within fintech, and collaboration with ML, Finance, and Product teams. The primary focus is on analytics and insights that support the company's AI-powered credit platform, rather than direct AI/ML model building.

What you'd actually do

  1. Own a core analytics domain within Credit Analytics (forecasting & valuation or risk capital), driving execution and continuous improvement of frameworks that power portfolio monitoring, planning, and decision-making
  2. Develop and enhance credit forecasting and valuation methodologies, including loss forecasting, scenario analysis, and portfolio performance measurement, ensuring outputs are accurate, explainable, and decision-useful
  3. Contribute to risk capital analytics and reporting, supporting funding strategies such as securitizations, warehouse facilities, and forward-flow programs through robust performance tracking, stress scenarios, and risk/return analysis
  4. Translate analytics into business impact, delivering clear insights and recommendations that guide product strategy, credit policy, and funding decisions
  5. Partner cross-functionally with ML, Finance, Product, Engineering, and Capital teams to align on definitions, metrics, and frameworks, and to integrate analytics into core workflows and decision processes

Skills

Required

  • 7+ years of experience in analytics, credit risk, or quantitative finance within fintech, financial services, or related industries
  • Experience building or applying credit risk / loss forecasting, portfolio analytics, or valuation frameworks in consumer lending or similar domains
  • Exposure to risk capital or structured finance concepts (e.g., securitizations, warehouse facilities, forward flow, or investor reporting)
  • Strong analytical and technical skills, including proficiency in SQL and at least one programming language (Python or R), and experience working with large datasets
  • Ability to translate complex analyses into clear, actionable insights for both technical and non-technical stakeholders

Nice to have

  • Experience partnering with ML / data science teams, particularly in underwriting or model performance monitoring
  • Familiarity with capital analytics, deal economics, and risk/return frameworks
  • Experience building or improving analytics infrastructure (data models, dashboards, automated reporting, GenAI solutions)
  • Exposure to model governance, controls, or audit processes (e.g., SOX, model validation, valuation reviews)
  • Demonstrated ability to influence cross-functional stakeholders and drive alignment across teams

What the JD emphasized

  • credit forecasting & valuation
  • risk capital analytics
  • credit forecasting and valuation methodologies
  • loss forecasting
  • scenario analysis
  • portfolio performance measurement
  • risk capital analytics and reporting
  • funding strategies
  • securitizations
  • warehouse facilities
  • forward-flow programs
  • performance tracking
  • stress scenarios
  • risk/return analysis
  • credit policy
  • funding decisions
  • analytics infrastructure
  • data models
  • pipelines
  • dashboards
  • reporting tools
  • credit models
  • analytics outputs
  • credit risk
  • quantitative finance
  • consumer lending
  • risk capital
  • structured finance
  • model governance
  • controls
  • audit processes
  • model validation
  • valuation reviews