2027 Winter - GRM, AI & Stress Testing Analytics Intern (4 Months)

0000050007 Royal Bank of Canada; Toronto; Hybrid; CAD 40,000 - 52,000; Full time

Benefits offered by this job

Mentorship

Flexible work arrangements

Student placement

Job summary

Royal Bank of Canada is offering a Winter 2027 student co-op in Group Risk Management in Toronto. You will develop Python-based tools, apply generative AI to risk problems, and build dashboards to communicate stress testing results to technical and non-technical stakeholders.

You will work with quantitative analysts, gather requirements, prototype AI-enabled monitoring, and participate in design sessions. The term runs January to April 2027 with a 37.5-hour week.

Qualifications

• Currently enrolled in a post-secondary program in a quantitative discipline.
• Working knowledge of Python to manipulate and validate large datasets.
• Working knowledge of SQL and querying relational data.
• Strong quantitative and analytical problem-solving abilities with attention to detail.
• Hands-on experience with generative AI/LLMs, including prompt engineering.
• Advanced Excel and MS Office skills; ability to present data clearly.

Responsibilities

• Develop Python-based analytical tools and automation for stress testing.
• Apply generative AI and LLMs to risk problems and report production.
• Analyze stress test outputs to explain drivers of losses and capital impact.
• Build interactive dashboards and visualizations (Python, HTML-based).
• Prototype AI-enabled risk monitoring platforms and document requirements.
• Collaborate with quantitative analysts and downstream users; share learnings.

Skills

Analytical skills

Problem solving

Self-starter

Attention to detail

Prompt engineering

Team collaboration

Education

Post-secondary quantitative program

Tools

Python

SQL

Tableau

HTML dashboards

Job description

What will you do?

• Develop Python-based analytical tools and automation that support stress testing processes, results analysis and benchmarking.
• Apply generative AI and LLM tools to real risk problems — scenario narrative drafting support, document and news analysis for emerging risk signals, code generation and quality checks, and automated report production.
• Analyze stress testing outputs to explain drivers of projected credit losses and capital impacts, and prepare clear summaries for technical and non-technical stakeholders.
• Build interactive dashboards and visualizations (Python, and HTML-based) that make stress testing results easier to interrogate and consume.
• Contribute to prototyping work on AI-enabled risk monitoring and stress testing platforms — from gathering requirements through to testing and documentation.
• Participate in design sessions with quantitative analysts and downstream users, contribute ideas, document requirements and share what you learn with the team.

What do you need to succeed?

Must-have

• Currently enrolled in a post-secondary program in a quantitative discipline (e.g. Data Science, Statistics, Mathematics, Computer Science, Engineering, Finance or Economics).
• Working knowledge of Python, with the ability to manipulate, analyze and validate large datasets.
• Working knowledge of SQL and comfort querying relational data.
• Strong quantitative, analytical and problem-solving skills, with careful attention to detail and data accuracy.
• Hands-on experience with generative AI or LLM tools, including effective prompt engineering.
• Strong MS Office skills, particularly Excel (advanced formulas and data manipulation), PowerPoint and Word.
• Intellectual curiosity and a self-starter mindset — comfortable asking questions and picking up new tools quickly.

Nice-to-have

• Exposure to credit risk, macroeconomics or econometrics coursework, including regression, time series or forecasting techniques.
• Familiarity with stress testing or regulatory capital concepts (CCAR, IFRS 9, Basel).
• Interest in how AI agents, retrieval-augmented generation and MCP integrations can be applied to production analytics workflows.
• Experience with data visualization tools such as Tableau, or building HTML-based or web dashboards.
• Exposure to SAS, R, or large-scale enterprise data environments.
• Familiarity with version control and collaborative development practices (Git).
• Ability to explain technical results in plain business language to non-technical partners.
• Strong organizational and time-management skills, with the ability to balance recurring deliverables against ad-hoc requests.

What's in it for you?

• Direct exposure to how a global bank measures resilience under stress, and to the regulatory programs that shape it.
• Mentorship from a team of quantitative and technical experts, with visibility to senior risk management stakeholders.
• A dynamic, collaborative and high-performing team that invests in developing its students.

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 ; orIf 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.

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.

Job Details

• Address: RBC CENTRE, 155 WELLINGTON ST W: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: 2026-08-27
• Application Deadline: 2026-09-21
• Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

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