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Toronto, Ontario, Canada
Hybrid
Job Description
Analyze credit risk and portfolio data to identify top and emerging risks and trends within the commercial book.
Support the preparation of monthly and quarterly risk reporting for various stakeholders, and respond to ad-hoc requests from partners across the business.
Contribute to deep-dive analyses on industry sectors within the commercial portfolio (e.g., commercial real estate), including supporting related data infrastructure and tooling work.
Build hands-on skills across the full data lifecycle — extraction, transformation, aggregation, interpretation and recommendation — with an emphasis on translating data into credit risk business decisions.
Participate in analytics design sessions: contribute ideas, gather and document business requirements, and help shape the reporting frameworks behind effective risk management.
Apply technical tools — including Excel, SQL, Python and data visualization software — to support credit risk analysis, with exposure to emerging tools such as generative AI as force-multipliers for the work.
Must-have
Currently enrolled in a post-secondary program in a quantitative discipline (e.g., Finance, Economics, Data Science, Statistics, Mathematics, Computer Science, Engineering or related field).
Strong analytical and problem-solving skills, with a keen eye for detail and data accuracy.
Solid technical and data skills, including working knowledge of Excel (advanced formulas and data manipulation), SQL (querying and manipulating large datasets), and Python (data analysis) — you'll be supporting real data preparation and deep-dive work, so a genuine comfort level with these tools matters.
Working knowledge of a data visualization tool, such as Tableau.
Ability to translate complex data into clear, plain-language insights for non-technical stakeholders.
Strong MS Office skills (Excel, PowerPoint, Word).
Strong organizational and time management skills, with the ability to balance recurring reporting deadlines against ad-hoc requests.
Intellectual curiosity and a self-starter mindset — comfortable learning new tools and asking questions.
Nice-to-have
Familiarity with commercial lending concepts and credit risk fundamentals (e.g., credit assessment, risk ratings, portfolio risk management).
Exposure to financial statement analysis.
Understanding of macroeconomic trends and their impact on credit and commercial portfolios.
Familiarity with the financial services industry.
Hands-on experience with generative AI or LLM tools, and an interest in applying AI to credit risk analytics.
Exposure to large-scale enterprise data environments, such as an Enterprise Data Warehouse (EDW), Enterprise Data Lake (EDL) or Hadoop-based platforms.
Please note: This posting is for a 4-months Winter 2027 Student placement with a start date of January 2027, and end date of April 2027. In order to be eligible for this 4-months Student position, you must either:
Please ensure that you meet these eligibility requirements before applying - candidates who apply but are found to be ineligible are not able to be considered.
We encourage you to apply as soon as possible as we accept applications on a rolling basis, but please note that the formal application deadline is September 20, 2026. Should you be selected to progress, someone from our team will reach out directly to provide instructions on next steps. Otherwise, feel free to check for progress updates by logging in to your RBC profile. If the status has not changed, it denotes the fact that your application is still under review.
RBC is committed to supporting flexible work arrangements when and where available. The successful candidate for this role will be required to be located within Ontario for the duration of the work term. Details regarding the specific virtual, hybrid, and in-office arrangements for this Integrated Learning/ Co-op position are to be discussed with the Hiring Manager.
ET27
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Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above
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