Lead Credit Risk Analyst
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We are a rapidly growing company that’s revolutionizing the way the restaurant industry does business by pairing technology with an extraordinary commitment to customer success. We help restaurants streamline operations, increase revenue, and deliver amazing guest experiences through our platform that combines restaurant point of sale, guest-facing technology, and award-winning customer support. Join us as we empower the restaurant community to delight guests, do what they love, and thrive.
Toast Capital provides fast, flexible funding to restaurants on the Toast platform, using Toast’s rich operational and transaction data to deliver financing aligned with how restaurants actually run. As Toast Capital scales, we are modernizing credit risk through better analytics, automation, and AI-enabled workflows.
Bready* to make a change?
The Fintech Risk team drives risk informed growth for Toast’s rapidly expanding Fintech business. 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 and you will build the AI-enabled tooling that lets a small team run that strategy at scale. If you have an analytic and data driven mindset, an eye for detail, curiosity about AI and automation, and a can-do attitude, this role is for you.
About this roll* (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
Do you have the right ingredients*? (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
- Masters 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
AI at Toast
At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.
Our Total Rewards Philosophy
We strive to provide competitive compensation and benefits progr...
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About Toast
Learn more about Toast and their company culture.
Restaurant technology company offering point-of-sale, payments and operations software.
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