2027 Winter – GRM, Portfolio Risk & Credit Analytics Intern (4 Months) at RBC

RBC; Toronto; On-site; CAD 20,000 - 25,000; Full time

Job summary

RBC in Toronto is seeking a Winter 2027 Student for a four-month, on-site placement in Group Risk Management. The role focuses on capital markets credit risk analysis, data preparation and reporting, and translating insights into risk decisions.

You’ll work with Excel, SQL, Python and Tableau, support ad-hoc requests, and participate in the full data lifecycle from extraction to interpretation. You must be enrolled in a quantitative program and able to balance deadlines with priorities.

Qualifications

• 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).
• 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 wholesale 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.

Responsibilities

• Analyze credit risk and portfolio data to identify top and emerging risks and trends within the wholesale credit 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 Capital Markets portfolio (e.g., Real estate and related), 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.

Skills

Analytical skills

Attention to detail

Excel

SQL

Python

Tableau

Communication with stakeholders

Problem solving

MS Office

Education

Quantitative program (Finance, Economics, Data Science, Statistics, Mathematics, CS, Engineering)

Tools

Tableau

Python (data analysis)

Job description

Job Description

This Full time on site position offers great opportunities for career growth.

What is the Opportunity?

The Capital Markets Risk Oversight team will assist in communicating and providing valuable insights to senior leadership on the performance of the Capital Markets portfolio and help promote a “Best of Class” risk oversight environment.

What will you do?

• Analyze credit risk and portfolio data to identify top and emerging risks and trends within the wholesale credit 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 Capital Markets portfolio (e.g., Real estate and related), 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.

What do you need to succeed?

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 wholesale 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.

Eligibility Requirements

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:

• Be returning back to school after the work term end-date of April 2027.
• If you are not returning back to school (i.e. are graduating in April 2027), you must require the full 4-months work term as a mandatory component to in order to graduate successfully.

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.

Additional Job Details

• Address: ROYAL BANK PLAZA, 200 BAY ST:TORONTO
• City: Toronto
• Country: Canada
• Work hours/week: 37.5
• Employment Type: Full time
• Platform: GROUP RISK MANAGEMENT
• Job Type: Student/Coop (Fixed Term)
• Pay Type: Salaried
• Posted Date: 2026-08-26
• Application Deadline: 2026-09-21

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Qualified applicants may be contacted to review their resume in more detail.