Analyst, Credit Risk

Location

500 Lake Shore Boulevard West, Toronto, Ontario, M5V 2V9

When you hire great people, great things can happen.

PC Financial offers unprecedented value to Canadians through payment products. We’re a different kind of bank with a different type of team—we’re collaborative and supportive and have the freedom and responsibility to thrive. Our purpose is to make the everyday simple and better for our customers, and we strive to make every dollar worth more.

Proudly serving over 3 million customers, PC Financial continues to grow by offering payment solutions and services that reward our customers every day. As a subsidiary of Loblaws Company Inc., we share the CORE values of Care, Ownership, Respect and Excellence. We are dedicated to helping Canadians Live Life Well. Join us on our journey.

• Collaborate with cross‑functional teams to develop and enhance expected credit loss models, ensuring compliance with regulatory requirements and industry standard processes.
• Conduct in-depth data analysis and interpret complex financial data to identify patterns, trends, and potential risks.
• Apply statistical techniques and quantitative methods to validate, calibrate, and back‑test credit risk models.
• Engage with partners to understand business requirements and translate them into analytical solutions that enhance decision‑making processes.
• Create insightful reports, presentations, and dashboards to communicate model outputs, findings, and recommendations effectively.
• Stay updated on emerging industry trends, regulatory changes, and advancements in credit risk modeling methodologies to continuously improve existing models.
• Collaborate with the risk management team to implement model enhancements and provide ongoing support for model performance monitoring and validation.

• Bachelor's or Master's degree in a quantitative field such as Mathematics, Statistics, Economics, or related fields.
• Demonstrated experience in risk management, credit risk modeling, or a similar analytical role within the financial services industry.
• Strong proficiency in statistical modeling techniques, data analysis, and quantitative methodologies.
• Proficient in programming languages such as Python or R, with experience in data manipulation, analysis, and visualization.
• Excellent communication skills, with the ability to effectively convey complex concepts and findings to both technical and non‑technical partners.
• A passion for storytelling with data and the ability to uncover meaningful insights to drive business decisions.
• Detail‑oriented mentality, with strong problem‑solving and critical‑thinking skills.
• Familiarity with regulatory requirements related to credit risk models (IFRS 9, CECL, etc.) is a plus.
• Ability to work in a collaborative team environment and manage multiple priorities with a positive and adaptable attitude.