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Manager, Analytics, Retail Credit Risk Unsecured Lending

Job in Toronto, Ontario, C6A, Canada
Listing for: Scotiabank
Full Time position
Listed on 2026-02-28
Job specializations:
  • IT/Tech
    Data Analyst, Data Science Manager
  • Finance & Banking
Salary/Wage Range or Industry Benchmark: 100000 - 125000 CAD Yearly CAD 100000.00 125000.00 YEAR
Job Description & How to Apply Below

Title:

Manager, Analytics, Retail Credit Risk Unsecured Lending

Requisition
Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.

Shape the Future of Credit Risk & Analytics with Impact, Innovation, and Purpose

Are you passionate about leveraging advanced analytics, cutting-edge technology, and creative strategy to drive responsible growth and innovation in the financial sector? Do you thrive in a collaborative, data-driven environment where your insights directly shape the organization’s success? Join us as Manager, Pre-Approved Originations, Unsecured Lending, and play a pivotal role optimizing risk strategies for Canada’s retail unsecured lending portfolio—including credit cards, lines of credit, and overdrafts.

The Manager, Pre-Approved Originations, Unsecured Lending is a dynamic leadership position designed for a curious, motivated, and highly analytical professional eager to make an impact in credit risk management. You will be at the heart of our strategic decision-making, transforming vast amounts of consumer and portfolio data into actionable strategies that balance risk and reward, while supporting sustainable business growth. Your work will empower responsible lending decisions, influence senior leadership, and shape the direction of our organization in an ever-evolving market.

Is this role right for you? In this role, you will:

Innovate Credit Risk Strategies:
Develop and continuously enhance sophisticated credit risk approaches using predictive models, machine learning, and champion/challenger testing. Identify and implement new automation opportunities and leverage both traditional and non-traditional data sources to validate assumptions and drive strategy optimization.

Lead Advanced Analytics:
Dive deep into portfolio performance and customer behaviour trends. Translate complex insights into intuitive dashboards and reports using SAS, SQL, Power BI, and other visualization tools. Surface growth opportunities, uncover emerging risks, and proactively adjust strategies to maximize risk-adjusted returns.

Drive Automation & Process Improvement:
Streamline decisioning criteria for approvals, declines, limit assignments, and more. Champion efficiency through lean adjudication design and technical innovation, supporting seamless implementation of strategy changes across multiple technology platforms.

Collaborate & Influence:
Work closely with Product, Operations, Regulatory, Fraud, and Audit teams. Effectively communicate risk measures, represent the risk perspective across business lines, and foster a culture of active listening and clear, persuasive communication with stakeholders at all levels.

Support Strategic Initiatives:
Ensure all lending strategies align with the Bank’s Risk Appetite Framework and support core business priorities—from new product launches to process improvements and acquisitions. Identify opportunities for policy and procedure enhancements to improve productivity and performance.

Ensure Compliance & Integrity:
Maintain adherence to Canadian regulatory standards and internal audit requirements, providing timely and effective support for investigations and solutioning as needed. Collaborate with Fraud and Security teams to ensure robust risk controls.

Do you have the skills that will enable you to succeed in this role? - We’d love to work with you if you have:

Required Qualifications

Bachelor’s degree or higher, or equivalent work experience.

Minimum 2-5 years’ experience in risk/portfolio management, preferably within a retail lending or credit risk management environment.

Proficiency in analytical programming and database tools (SAS, SQL, Python, or equivalent). Experience applying advanced statistical methodologies and machine learning techniques is considered a strong asset.

Demonstrated ability to translate complex data into clear dashboards and actionable business insights, using visualization tools like Tableau, Power BI, or Excel (Pivot Tables).

Excellent communication, relationship management, and analytical problem-solving skills. Able to engage and influence stakeholders at all levels.

Strong understanding of credit…

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