Description
We are seeking a Lead Credit Risk Strategist focused on the acquisition space. You will analyze customer characteristics, identify risk differentiators, and recommend underwriting strategies that meet our risk and return goals. You will also build the AI-enabled tooling that lets a small team run that strategy at scale.
Responsibilities:
- Work with the leadership team to develop and refine credit risk strategy for new and existing lending products
- Identify risk drivers and recommend policy changes that balance risk and growth
- Partner with Data Science to build, test and monitor credit risk and decision models
- Perform portfolio analysis to monitor credit performance, emerging trends, and opportunities to expand or tighten strategy
- Design and execute A/B tests and champion-challenger experiments for policy, pricing and strategy changes
- Support risk-based pricing and profitability analysis to improve risk-return outcomes
- Build AI-enabled workflows and copilots that automate recurring analysis, summarize merchant performance, and surface risk signals, anchored to deterministic metrics with human oversight on every decision
- Collaborate with R+D, Product, Engineering, Data Science and Operations to launch new products, features, and AI-enabled workflows
Requirements:
- 5+ years in retail/consumer/SMB credit risk or strategy, preferably in fintech or banking
- Past experience in growing a lending business and hands-on experience in credit strategy is required
- Ability and experience in writing credit memos and credit decision and strategy documentation
- Experience applying AI or LLM tools to improve analytical workflows, operational processes, or decision support
- Advanced SQL and Python/R, with Looker/Tableau/Hex or similar; familiarity with statistical modeling and A/B testing
- Working knowledge of model governance, explainability and fair lending in automated credit decisioning
- Master's Degree or higher in a quantitative field (Mathematics/Statistics/Economics/OR/Business)
- Ability to influence a cross-functional, non-hierarchical environment to drive progress across Risk, Engineering, Data Science and Product