Credit Risk Manager

Strong proficiency in SQL and Python is required. A solid grasp of credit risk principles for SMB or consumer lending, including repayment modeling, vintage analysis, and concentration risk. Experience building dashboards and analytical tools using platforms like Sigma, Looker, Tableau, or Metabase. Ability to utilize AI tools to dramatically increase speed and output quality. Bachelor’s degree in a quantitative or analytical field (e.g., Economics, Finance, Mathematics, Statistics, Engineering, or Computer Science). 3+ years of experience in credit risk, analytics, fintech lending, specialty finance, or adjacent fields.

Develop and own the analytical framework for credit risk, including underwriting models, loss forecasting, and credit policy definition using SQL and Python. Construct comprehensive dashboards to track repayment behavior, vintage performance, delinquency roll rates, and unit economics. Analyze product performance to recommend data-backed changes to product designs that maximize funding availability while protecting downside. Conduct deep-dive assessments on market segments and risk profiles to help design and launch future financial products for real estate agents. Leverage AI tools to accelerate code generation and insight discovery, moving risk processes from manual reviews to automated decisioning. Partner closely with Product, Finance, and Operations leadership to translate complex risk data into clear, actionable business strategies.