Final date to receive applications:
01/30/2026Address:
33 Dundas Street WestJob Family Group:
Strategy & ChangeJoin 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. Develops and maintains risk decision-support strategies using analytical solutions to enable high-quality, fact-based decisions for a designated risk portfolio. Supports the development of the strategy and roadmap for data quality, data analytics, data modeling, reporting, business intelligence, and the design and development of sophisticated decision support tools.
Leads the development and supports the execution of Retail product suite credit strategies (i.e. Unsecured Lending, Real Estate Secured Lending or Business Banking) to drive ROE-accretive primary customer growth and full customer relationships while optimizing risk-return outcomes within prescribed Board approved risk appetite. Defines 1
LOD business requirements for supporting predictive models developed in 2
LOD to accurately estimate risk, ensuring sophistication and connectivity across the retail credit ecosystem, i.e., granular customer segments, behavioural data, active model lifecycle management. Owns the end-to-end credit customer journey for their retail credit product suite, and the connectivity across the customer lifecycle (i.e. acquisition, account management, collections strategies) with agile targeting, treatments and actions responsive to the dynamic macroeconomic environment.
Develops portfolio monitoring, continuous improvement and calibration of early warning signals to ensure early indications of elevated risk are proactively identified, with accurate loss forecasts, downturn readiness, and timely adjustments and de-risking strategies and actions, and are connected to customer experience, acquisition, account management and collections action plans.
Develops, maintains and supports the implementation of retail credit acquisition and account management strategies and decision support tools for their retail credit product suite that align with business requirements and risk appetite to optimize decisions and productivity and balance risk and profitability.
Brings together inputs (e.g. credit and marketing analytics, pricing, growth forecasts, etc.) to develop holistic business strategies to optimize P&L outcomes against set goals.
Develops proposals "in service" of Product teams, incorporating their strategic goals and aligning frequently on desired outcomes.
Develops pre-delinquency / collections / “placemat” strategies for their credit product suite, incorporating predictive modeling, forecasting and early warning analytics, to design targeted approaches for products, processes, channels etc. based on unique customer risk levels and financial behaviour, to optimize loss performance.
With Head, First Party Fraud Strategy, develops accurate credit proposals (incl. revenue and loss forecasts) and supports policy change proposals, using statistical models developed by 2nd line Modeling team and other analytical methods / tools to mitigate first party fraud losses.
Refines strategies to optimize through-the-cycle ROE within risk appetite and applicable regulation/internal policies, ensuring adherence to Key Risk Metrics (KRM) s.
Defines 1
LOD business requirements specific to the in-scope credit strategy, to support predictive models developed in 2
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