Credit Risk Analytics & AI Enablement Lead

Toast
Remote USPosted 3 April 2026

Job Description

Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy. Toast Capital provides fast, flexible funding to restaurants and hospitality businesses on the Toast platform. By leveraging Toast’s rich operational and transaction data, Toast Capital delivers financing that is aligned with how restaurants actually run. As Toast Capital scales, we are investing in modernizing our credit risk organization through better analytics, automation, and AI-enabled workflows. Our goal is to empower risk analysts with tools that improve decision quality, reduce manual work, and allow the team to scale efficiently. The Fintech Risk team at Toast is accelerating the adoption of AI to transform how we operate. We are seeking a Lead Analyst to design and deploy intelligent, AI-powered workflows for Toast Capital’s credit risk function. This role sits at the intersection of credit risk, analytics, and applied AI. You will identify opportunities to improve underwriting, portfolio monitoring, and risk operations by designing and implementing internal AI tools such as copilots, assistants, and automated analytical workflows. The ideal candidate combines strong credit risk intuition, analytical problem-solving, and technical curiosity about AI tools and automation. You should be excited about turning manual analytical processes into scalable systems that allow risk teams to operate faster and more consistently. A day in the life (Responsibilities) Identify high-impact opportunities to improve credit risk workflows using AI across underwriting, portfolio monitoring, policy interpretation, and collections Design and deploy internal AI copilots that help analysts draft credit memos, summarize merchant performance, and interpret key risk signals Build tools that automatically generate risk narratives, portfolio commentary, and merchant-level performance summaries Partner with Engineering, Data Science, and Product to implement AI-powered tools using structured data, internal APIs, and secure LLM platforms Develop prompt frameworks and workflows that combine deterministic risk metrics with AI-generated insights while maintaining explainability and human oversight Conduct portfolio analyses to identify merchant performance trends and emerging risk signals Redesign risk processes to reduce manual work, automate recurring analysis, and increase analyst productivity Collaborate with Credit Risk, Compliance, Engineering and Operations to responsibly deploy and scale AI-enabled workflows What you'll need to thrive (Requirements) 5+ years of experience applying analytics, automation, or AI to improve risk or operational workflows in fintech, financial services, or technology Experience applying AI or LLM tools to improve analytical workflows, operational processes, or decision support Strong analytical skills with the ability to translate portfolio or transactional data into actionable insights Advanced proficiency in SQL and Python; experience building dashboards or automated analytics solutions (Looker/Tableau/Hex or similar) Familiarity with prompt design, AI-assisted workflows, or automation frameworks integrating structured data with LLM outputs Strong communication skills and ability to influence cross-functional stakeholders across Risk, Engineering, Data Science, and Product AI at Toast At Toast 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 Spread* of Total Rewards We strive to provide comp ... (truncated, view full listing at source)
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