Senior Credit Risk Analyst
Félix · Washington, DC · 3 wk ago
RemoteRemoteFinance$100/hrFull-time
Responsibilities
- Lending Portfolio Leadership: Act as the lead credit analytics owner for the SNPL team, serving as the source of truth for credit insights.
- Executive Reporting: Own and deliver executive-level reporting regarding portfolio health, NPL (Non-Performing Loans) trends, and macroeconomic risk factors.
- Financial Modeling: Own and continuously optimize valuation frameworks, vintage analysis, and Net Present Value (NPV) credit models.
- Framework Architecture: Support, design, and build end-to-end credit analytics frameworks for SNPL and future digital credit products.
- Acquisition Credit Policy: Direct and manage the Acquisition Credit Policy, optimizing approval rates while keeping default risk tightly within target bands.
- Credit Monitoring & Surveillance: Maintain constant surveillance on credit distribution and reporting across multiple demographic cohorts.
- Customer Management Policy: Build, test, and iterate on Customer Management Credit Policies (e.g., credit limit increases/decreases, re-engagement rules).
- Model Integration & Testing: Partner with engineering to integrate new scoring models and champion-challenger testing mechanics directly into our production portfolio performance.
- Alternative Data Exploration: Research, validate, and integrate external alternative data sources (e.g., bureau data, behavioral analytics) to enhance predictive models.
Requirements
- Consumer Lending Pedigree: 4+ years of deep analytical experience in Credit Risk, explicitly managing unsecured consumer lending, credit cards, or digital lending products.
- Rigorous Analytics Toolkit: Expert level in SQL and statistical data modeling (Python/R, dbt, or similar data infrastructures).
- Sharp Lending Judgment: Proven track record of evaluating and defining credit policies, understanding tradeoffs between growth volume and loss provisions.
- AI/ML Familiarity: Experience working alongside data scientists to evaluate and integrate predictive ML credit scorecards.
- Strong Communication: Ability to package complex portfolio metrics into clear, high-level executive summaries for the C-suite and investment partners.
- Bias for Action: Thrives in an environment of rapid experimentation, moving fast to adjust credit strategies based on instant user behavior trends.