Manager, Auto Finance Credit Strategy – RBC, Toronto, ON
Location: Toronto, ON | Company: RBC
RBC is hiring a full-time Manager, Auto Finance Credit Strategy in Toronto, Ontario, within Group Risk Management. This analytical role focuses on using data, statistical methods and machine learning to improve real-time credit decision-making for RBC’s Auto Finance business.
Based at RBC WaterPark Place at 88 Queens Quay West, the position combines credit risk strategy, predictive modelling, automation and cross-functional project delivery. The role follows a hybrid arrangement with four days per week on-site and works across Product, Sales, Operations and Risk Management teams.
About the Auto Finance Credit Strategy Role
The Manager, Auto Finance Credit Strategy supports decisions about how RBC can grow automotive loan originations while balancing credit risk, pricing, operational efficiency and customer impact. The work relies heavily on large data sets and quantitative analysis to identify patterns and develop strategies that can improve financial outcomes.
The position also involves designing automated approaches for real-time credit adjudication and improving the consistency of decisions that require manual review. Machine learning and statistical techniques are used to develop predictive models and support more informed lending strategies.
Key Areas of Responsibility
This role combines quantitative analysis, credit strategy development and end-to-end project ownership, with responsibilities extending from initial problem identification through implementation and ongoing monitoring.
Data Analysis
Analyze large data sets using empirical, statistical and machine learning techniques to identify issues and uncover insights that may improve business and financial outcomes.
Credit Strategy Design
Develop automated decision strategies that support real-time adjudication and improve the quality and consistency of manual credit decisions.
Predictive Modelling
Apply quantitative methods and machine learning techniques to behavioural data in support of credit strategy and risk assessment.
Stakeholder Collaboration
Work with teams across Product, Sales, Operations and Risk Management to align analytical solutions with broader Auto Finance priorities.
Project Management
Manage initiatives from concept and solution design through stakeholder approval, implementation and post-launch monitoring.
Decision Optimization
Use analytical evidence to help balance risk, pricing, efficiency and customer considerations within automotive lending decisions.
Education and Technical Requirements
RBC requires a bachelor’s degree in Computer Science, Statistics, Mathematics, Behavioural Economics, Engineering or another quantitative field. Candidates should also have at least one year of experience using programming or scripting languages such as SQL, Python, R or Java.
The position requires familiarity with extracting, transforming and loading different types of data, along with experience using GitHub and code management practices. Candidates should also be comfortable working in a Linux environment and using shell scripting.
Skills That May Help Candidates Succeed
The role requires a strong mix of quantitative capability, business judgement and communication. Candidates must be able to convert complex data into practical strategies while coordinating with stakeholders across multiple functions.
Interpreting large and complex data sets helps identify trends, risks and opportunities that can inform credit strategy decisions.
Statistical modelling and machine learning techniques support the development of predictive approaches for credit and lending decisions.
An understanding of credit risk concepts can help candidates evaluate how different strategies may affect loan quality and portfolio performance.
Strong analytical thinking is important for identifying issues, testing potential solutions and determining how changes may affect business outcomes.
Clear communication helps explain analytical findings and secure alignment from stakeholders involved in product, operations, sales and risk decisions.
Preferred Analytics and Technology Experience
RBC considers familiarity with credit risk concepts and data visualization tools such as Tableau to be useful assets. Experience with statistical techniques including linear and logistic models, gradient boosting, supervised learning, clustering, recommendation systems, time-series analysis and experimental design may also strengthen a candidate’s fit.
Additional exposure to technologies such as Apache Spark, Hadoop, Hive, public cloud platforms and data serialization formats including JSON and Parquet is also listed as beneficial. The position is a regular full-time salaried role with 37.5 work hours per week.
How to Apply
Candidates interested in the Manager, Auto Finance Credit Strategy position in Toronto can submit an application through RBC’s official careers website. The published application deadline is August 17, 2026.
Applicants should make sure their resume clearly reflects quantitative education, programming experience, data analysis work and any background in credit risk, machine learning, statistical modelling or financial services.
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