Description
We are seeking a Senior Manager, Credit Risk to join our Fintech department at Jobber. As a Senior Manager, Credit Risk, you 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.
Responsibilities:
- Lead, coach, and grow a team of Credit Risk Analysts
- 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
- Partner closely with Data Science and Risk Analytics to build, validate, and improve credit risk models and decisioning logic
- Champion an AI-native approach to credit risk management
- Set the multi-year roadmap for the credit risk function across people, models, data, and tooling
- 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
- Own credit loss provisioning and stress testing
- Report on credit risk exposure, portfolio health, and emerging trends to Fintech and Risk leadership, the executive team, and credit or risk committees
Requirements:
- 8+ years of experience in credit risk, in financial services, fintech, payments, or lending
- A track record of setting and owning credit policy, risk appetite, and limit frameworks
- Experience managing a credit portfolio through a period of stress or a full credit cycle
- A builder's mindset: a track record of solving problems through automation and tooling
- A deeply data-centric approach to decision-making
- Proficiency in SQL and Python
- Working familiarity with statistical and machine learning approaches used in credit risk management
- Hands-on experience with IFRS9 or equivalent GAAP standards
- Strong written and verbal communication skills