Job Summary
Job Description
What is the Opportunity?
As part of the Group Risk Management (GRM) – Credit Strategy team, the Credit Strategy and Data Science Manager role will analyze, design, optimize and implement solutions to enable real-time decision making for the retail lending businesses. The team specializes in leveraging large data sets to generate insights and make fact-based decisions on how to profitably grow loan originations by balancing risk, pricing, operational efficiency and customer impact.
The role employs a range of leading-edge technologies and capabilities, applying machine learning and statistical techniques, to build predictive behavioral models and credit strategies.
What will you do?
Develop quantitative credit risk metrics and tools to help manage, measure, and monitor credit risk.Use empirical, statistical and machine learning techniques to build financial models to simulate financial outcomes of strategy decisions, measure true outcomes against expectations and drive continuous improvement from findingsDesign automated credit strategies to improve real-time adjudication and the quality and consistency of manual adjudication.Support the implementation and ongoing integrity of credit strategies within appropriate systemsEngage cross-functional stakeholders across Product, Sales, Operations and Risk Management.End-to-end project management, from idea conception, solution design, stakeholder buy-in to implementation and monitoring.What do you need to succeed?
Must-have
Bachelor or Master’s degree in Computer Science, Statistics, Mathematics, Economics, Engineering, or other quantitative field of study.Expert critical thinker and problem-solverProficient in Excel, SQL and Python and code management best practicesProven experience in delivering high quality and accurate work with the ability to multitask and managing prioritiesEffective and conversant in both business and technical communicationsNice-to-have
Experience with data visualization tools such as TableauFamiliar with retail lending business and/or credit risk concepts.Experience applying statistical concepts including but not limited to: linear and logistic models, gradient boosting/XGboost, supervised statistical learning, clustering, recommendation systems, times-series analysis, experimental design (A/B testing).Exposure to Apache Spark, Hadoop and Public Cloud technologies, data serialization (JSON, Parquet, etc).Experience with big data processing tools like Spark and Hive.What’s in it for you?
We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.
A comprehensive Total Rewards ProgramLeaders who support your development through training and coachingWork with a dynamic, collaborative team with ability to make a differenceJob Skills
Credit Risks, Credit Strategies, Data Analysis, Data Science, Data Visualization Tools, Engaging Communication, Predictive Modeling, Python (Programming Language), Quantitative Analytics, Risk Management StrategiesAdditional Job Details
Address:
RBC WATERPARK PLACE, 88 QUEENS QUAY W:TORONTOCity:
TORONTOCountry:
CanadaWork hours/week:
37.5Employment Type:
Full timePlatform:
GROUP RISK MANAGEMENTJob Type:
RegularPay Type:
SalariedPosted Date:
2025-07-16Application Deadline:
2025-07-31Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above
Inclusion and Equal Opportunity Employment
At RBC, we believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.
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