Senior Manager of Credit Risk, Jobber

• 8+ years of experience in credit risk, in financial services, fintech, payments, or lending, including 3+ years of people leadership, ideally including hiring and developing team leads as well as analysts
• A track record of setting and owning credit policy, risk appetite, and limit frameworks, and of making and defending high-stakes credit decisions with incomplete information
• Experience managing a credit portfolio through a period of stress or a full credit cycle, and adjusting strategy as performance changed
• A builder's mindset: a track record of solving problems through automation and tooling, not just process, and genuine enthusiasm for using AI to build new approaches to credit risk rather than only applying existing ones
• A deeply data-centric approach to decision-making, with comfort working directly in the data rather than relying solely on others to produce it for you
• Proficiency in SQL and Python (or a similar language), enough to independently pull, analyze, and interrogate data, to review your team's analytical work, and to collaborate credibly with Data Science and Analytics
• Working familiarity with statistical and machine learning approaches used in credit risk management (e.g., logistic regression, decision trees, gradient boosting)—you don't need to be a data scientist, but you should understand what these approaches do, how they work at a conceptual level, and when it's appropriate to apply them, and what it takes to govern them in production (validation, drift monitoring, and explainability)
• Hands-on experience with IFRS9 or equivalent GAAP standards (e.g., CECL) for credit loss provisioning, including building or owning an expected credit loss model and the governance around it
• Strong written and verbal communication skills, with the ability to translate technical or quantitative findings into decisions that product, operations, and leadership stakeholders can act on, including presenting to executive leadership, credit committees, auditors, and external funding partners
• A genuine passion for fintech, and curiosity about how payments and lending products should manage risk differently than legacy financial institutions
• The ability to embrace ambiguity and change—we don't know what we don't know, so you should be comfortable coming in and improving the process rather than waiting for one to be handed to you
• The ability to work autonomously with strong time management skills. We are a mix of fully remote and hybrid distributed across the country. While you'll be part of a team, you'll need to be a self-starter who can find direction and guidance proactively

Desirable

• Fintech is one of the fastest-growing parts of Jobber, and a core strategic priority for us as a company. We're investing in this area because we believe embedding financial tools within our product deepens our ability to help small businesses be successful—whether that's helping them get paid through Jobber Payments, or, in the near future, offering them access to capital through a growing lending business
• Our Risk team is a critical part of the broader Fintech team, and core to Jobber's success. Credit Risk is responsible for the frameworks, models, and operational discipline that let us extend payments and lending products responsibly, protecting both our customers and Jobber from undue credit exposure
• The Senior Manager, Credit Risk will lead and grow a team of Credit Risk Analysts, owning the day-to-day operations of the credit risk function while helping build it into something more ambitious: an AI-native credit risk practice, built for Jobber Payments today and ready to scale into a growing lending business
• This is a role for a builder, not a doer—someone who looks at a manual process or an ad hoc decision and asks how it should be automated, modeled, or systematized, rather than simply executed by hand
• You'll work closely with Data Science and Risk Analytics to design and strengthen credit risk models, policies, and monitoring, and you'll partner cross-functionally across Fintech, Product, and Customer Support to make sure credit risk decisions are embedded seamlessly into the products our customers use every day
• Lead, coach, and grow a team of Credit Risk Analysts (and, as the function scales, the team leads who manage them), owning hiring plans, team structure, and career paths, and setting the standard for how the team investigates, decides, and communicates credit risk
• Own credit risk operations end-to-end: underwriting and exposure decisions, portfolio monitoring, collections and recovery strategy, and loss forecasting
• Define and maintain Jobber's credit risk appetite, credit policy, and limit framework (approval criteria, exposure and concentration limits, and delegated decision authority), and act as the final escalation point for high-exposure and exception decisions
• Partner closely with Data Science and Risk Analytics to build, validate, and improve credit risk models and decisioning logic, including scorecards, statistical models, and machine learning approaches where they add value
• Champion an AI-native approach to credit risk management, using AI and automation to build novel solutions to novel problems, not just to speed up existing workflows, and drive automation opportunities from idea through to implementation
• Set the multi-year roadmap for the credit risk function across people, models, data, and tooling, and make the case to leadership for the investment needed to deliver it
• Build and strengthen the credit risk function for Jobber's payments business today, and design and own the credit risk framework for a growing lending business
• Work cross-functionally with Fintech, Product, Finance, Legal, Compliance, and Customer Support teams to embed credit risk policy and controls into product and operational workflows
• Make sure credit policy and decisioning meet applicable Canadian and US requirements, partnering with Compliance and Legal on fair lending, adverse action and decline notices, commercial financing disclosures, and regulatory change
• Own credit loss provisioning and stress testing: build expected credit loss methodology, forward-looking scenarios, and management overlays from IFRS 9 or equivalent GAAP standards, and turn scenario results into loss forecasts, limit changes, and funding plans, partnering with Risk Analytics and Finance
• Report on credit risk exposure, portfolio health, and emerging trends to Fintech and Risk leadership, the executive team, and credit or risk committees
• Partner with relevant teams on the credit side of funding the lending book (for example, warehouse facilities or forward-flow partners), including loss and performance forecasts, eligibility criteria, loan-level data tapes, and lender due diligence
• Lead broader Fintech and Risk initiatives on credit-risk-relevant topics, including new product launches
• Own relationships with credit data and decisioning vendors (credit bureaus, bank-data and open banking providers, decisioning platforms), from evaluation and contracting through ongoing performance oversight