Jobber - Manager, Credit Risk

• Demonstrated experience in credit risk, in financial services, fintech, payments, or lending, including people leadership or mentorship of an analyst team. • 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 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. • Familiarity with IFRS9 or equivalent GAAP standards (e.g., CECL) for credit loss provisioning, or a strong ability to learn and apply this quickly. • 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. • 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. • It would be really great (but not a deal-breaker) if you had: • Familiarity with credit scorecards, including scorecard development, calibration, or monitoring. • Experience building or overseeing credit risk models or policies for a lending product (installment loans, lines of credit, merchant cash advances, or similar). • Experience with modern payments or lending infrastructure (e.g., Stripe, Adyen, Plaid, or similar). • Experience working with or evaluating AI/ML tooling or vendors for risk decisioning. • Familiarity with Slack, Salesforce, Asana, Confluence, or other collaboration tools. • For extended remote roles:We believe great collaboration is intentional, and that means coming together in person to build, brainstorm, and connect from time to time. This role is open to candidates anywhere in Canada. Employees who live in one of our hub cities—Edmonton, Toronto, Vancouver, or Kitchener-Waterloo—will participate in their department's in-office schedule, while employees outside our hub cities will work remotely. • For extended remote roles: