Position Title: Data Analytics Manager- 4 Line of Business / Business Group: Global Risk Management – Canadian Banking (unsecured lending) Start Date: August 31st, 2026, Contract Duration: 6 months Hybrid - 3 days/week (Monday, Wednesday, Thursday), may increase to 4 Location - Downtown, Toronto Schedule Hours: Monday to Friday and 37.5/hr week Possibility of Overtime: No Possibility of Extension: TBD Possibility of FTE: No

Story Behind the Need:

The Manager, Portfolio Analytics & Insights, is responsible for delivering high-quality portfolio monitoring, analytics, and insights for the Unsecured Lending portfolio. The role operates as a senior individual contributor with emerging leadership responsibilities, supporting the Senior Manager/Director in driving data-driven decision-making, enhancing monitoring capabilities, and informing risk strategies. This position combines strong technical execution with business acumen and effective communication to translate portfolio performance into actionable insights for senior stakeholders.

Candidate Value Proposition:

The successful candidate will gain meaningful exposure to the unsecured lending and credit domain. Join a high‑performing, purpose‑driven analytics team shaping Canada’s retail unsecured lending strategy. Work directly with real credit card and ULOC performance data. Build and enhance dashboards, recurring reports, and analytical insights used by business and risk leaders. Grow into ownership of defined reporting or strategy components. Use modern analytics tooling including SQL, Python, SAS, Power BI/Tableau, and risk analytics frameworks. Role Responsibilities / Typical Day in Role:

1. Portfolio Monitoring & Analytics Design, develop, and maintain portfolio monitoring dashboards and scorecards (Power BI or equivalent) covering: Credit performance, delinquency trends, losses, PCL, vintages, and early warning indicators Perform deep-dive analytics to investigate portfolio trends, variances, and emerging risks Analyze performance across acquisition channels, programs, and segments to identify key risk drivers Execute complex data extraction, transformation, and analysis using SQL, SAS, Python, and/or Excel

2. Insights Generation & Data Storytelling Translate analytics into clear, structured, and actionable insights for senior leadership Support development of executive-ready materials for governance forums, regulatory requests, and business reviews Provide recommendations to improve portfolio performance, credit quality, and risk-adjusted returns Delivering timely and high-quality responses to ad-hoc analytical requests

3. Data Management, Quality & Controls Ensure data accuracy, integrity, and consistency across reporting and analytics outputs Perform reconciliation, validation, and quality control checks across multiple data sources Proactively identify and resolve data issues, gaps, or inconsistencies Maintain documentation on data logic, definitions, and methodologies to support audit and governance requirements

4. Process Enhancement & Automation Identify opportunities to improve efficiency, scalability, and consistency of reporting processes Drive automation and standardization initiatives using SQL, SAS/Python, and BI tools Contribute to the evolution of portfolio monitoring frameworks and data infrastructure

5. Stakeholder Collaboration & Business Support Partner with stakeholders across Product, Finance, Collections, and Strategy teams to support initiatives such as: New programs or policy changes Credit strategy adjustments Portfolio risk assessments Provide subject matter expertise on portfolio performance and risk drivers Build strong working relationships and influence decision-making through data-driven insights

Performance Measurement: Filling and Time management of Project 1 on 1 with Manager on performance

Candidate Requirements/Must Have Skills:

1. 8+ years’ experience in data/statistical analysis
2. 5+ years’ experience with large datasets using SAS, SQL, Python
3. Experience converting SAS/SQL code to Python code

Nice-To-Have Skills:

1. Retail credit risk knowledge, especially credit cards and ULOC – is a strong preference
2. Experience with consumer credit performance data & risk metrics
3. Experience working in financial services analytics environments
4. Experience with data visualization & reporting tools: Power BI, Excel

Soft Skills:

Strong analytical thinking and problem-solving skills High attention to detail and data accuracy Effective communication and data storytelling Ability to balance multiple priorities in a fast-paced environment Ownership mindset with a proactive approach to identifying opportunities Educational Requirements: Bachelor’s degree in quantitative or business discipline (e.g., Mathematics, Statistics, Economics, Finance, Computer Science) Graduate degree considered an asset

Best VS. Average Candidate:

The ideal candidate demonstrates strong analytical skills using SAS and SQL, combined with familiarity in credit risk data and the capability to turn data into meaningful insights. Experience with retail banking products—especially credit cards and ULOC—will significantly differentiate top candidates.

Interview Process:

1st Round: Panel interview / Ben and or Stassi/ 60 minutes/ technical question and behavioral question/ In Person/

2nd Round: HM and another manager/ 30 minutes/ In person/ Behavioral and culture fit.

Red Flags :

Limited exposure to credit portfolio analytics, risk performance metrics, data quality controls, or stakeholder-facing analytics roles within a financial services environment. Less than 8 years of hands-on data analytics experience or insufficient proficiency in SAS, SQL, and Python, including experience working with large, complex datasets.