Overview

Application Deadline: 10/13/2026 Address: 33 Dundas Street West Job Family Group:Audit, Risk & Compliance Join a pioneering team shaping the future of Canadian Retail Credit Strategies.We're building next-generation, end-to-end credit solutions that span the entire lifecycle-from acquisition and account management to collections-anchored in a holistic Lending Decision Strategy and aligned with Canadian Personal & Business Banking (P&BB) priorities.Our approach combines cutting-edge decisioning software, advanced decision trees, and innovative credit models to deliver smarter, faster, and more customer-centric outcomes. This is your opportunity to influence credit cycles using modern modeling techniques and best-in-class decisioning applications, all within a high-performance, customer-focused environment.If you're passionate about leveraging data, technology, and strategy to transform lending decisions and drive meaningful impact across Canadian P&BB, this is the team for you. The Manager, Unsecured Lending & Strategy Optimization is responsible for developing advanced analytical, machine learning, and AI-enabled capabilities to improve strategy effectiveness across Credit Cards and Personal Lending portfolios. The role applies large-scale structured and unstructured data to forecast strategy outcomes, uncover emerging risk and growth signals, identify customer and portfolio trends, and build decision frameworks that balance profitable growth, enhanced customer experience, and the bank's risk appetite. As part of Unsecured Lending Strategy team, the Senior Manager translates data science innovation into practical strategy applications across acquisition, account management, exposure optimization, customer engagement, early warning, and portfolio performance management, while collaborating with Product, Risk, Technology, Analytics and Operations partners to support execution. Key Accountabilities Data Science & Predictive ModelingDevelop and apply machine learning, statistical, and AI-enabled models to improve strategy decision-making across the customer lifecycle.Mine large-scale structured and unstructured data to identify new predictive variables, customer attributes, behavioural signals, and early warning indicators.Design feature engineering approaches that improve decision segmentation, customer targeting, pricing, limit management, and treatment optimization.Build predictive frameworks to estimate customer response, credit performance, profitability, attrition, engagement, and other strategy outcomes.Evaluate the incremental value, stability, explainability, and business usability of new variables before recommending use in strategy decisioning.Create simulation and forecasting capabilities to assess the expected financial and risk impact of strategy changes before implementation.Apply AI innovation and emerging capabilities by evaluating and piloting machine learning, Generative AI, big data, and optimization techniques that enhance strategy decisioning and portfolio management, with a focus on scalable use cases, measurable business value, implementation readiness, and appropriate governance.Act as a key model user, applying models and scores within strategy logic, ensuring proper interpretation and segmentation to differentiate risk across the portfolio. Strategy Optimization & Decision ScienceDesign and implement customer-level lending strategies using decision tree and optimization platforms, aligning treatments to growth, profitability, customer experience, and risk objectives.Contribute to strategy design across acquisition, credit limit management, exposure optimization, early warning treatments, and performance-based interventions, ensuring alignment across the customer lifecycle.Execute structured Champion-Challenger testing frameworks to evaluate and refine treatments, segmentation schemes, decision pathways, and business rules.Collaborate with Technology and Analytics teams to translate strategy logic into de