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Student Internship, Quantitative Credit Risk Analyst

VersaBank -
London, ON

Apply Now

Job details

Full-time

Qualifications

NumPy
R
Pandas
Risk management
Data visualization
Python
Analytics

Full job description

VersaBank is an inclusive, entrepreneurial, Schedule 1 Chartered Bank with over $5.8 billion in assets and growing . As Canada’s most innovative bank, VersaBank operates as a branchless financial institution that obtains its deposits and provides most of its loans and leases electronically, with innovative deposit and lending solutions for financial intermediaries that allow them to excel in their core businesses.

VersaBank’s Common Shares trade on the Toronto Stock Exchange (“TSX”) and Nasdaq under the symbol VBNK. Our head office is in London, Ontario, with various offices located across Canada. For more information on VersaBank , please visit our website at www.versabank.com .

VersaBank is seeking a quantitative student for a summer position focused on developing statistical analysis to determine the appropriate buffer required to absorb cash-flow interruptions from overdue loans and leases .

This role is ideal for a student who enjoys applied statistics, real-world data, and is motivated by analytical work that will directly inform credit-risk decisions.

In this role, you will analyze historical cash-flow performance from a range of lenders, identify the drivers of 90-day payment stoppages, and help build a statistically defensible framework for determining the buffer required to absorb these interruptions. You will also be involved in data cleaning, model development, and interpret ing results for senior management.

Primary Responsibilities include:

Analyze 10-year historical cash-flow streams from multiple lenders.

Identify predictors of 90-day delinquency and payment stoppages.

Develop statistical models to estimate required buffers for cash-flow interruptions.

Conduct regression, time-series, and vintage/cohort analyses.

Clean, merge, and validate large datasets from external sources.

Prepare clear summaries, visualizations, and recommendations for internal stakeholders.

Document methodology to ensure reproducibility and auditability.

Qualifications:

Currently enrolled in a Statistics, Actuarial Science, Data Science, Economics, Finance, Mathematics, or Computer Science program.

Strong academic performance in quantitative subjects .

Proficiency in Python (pandas, NumPy, stats models , scikit-learn) or R.

Solid understanding of r egression analysis , p robability and distributions , and t ime-series or econometrics .

Experience working with messy, real-world datasets.

Ability to communicate analytical findings clearly and concisely.

Exposure to survival analysis or hazard models is an asset.

Familiarity with credit-risk concepts (delinquency, default, recovery) is an asset.

Experience with data visualization tools is an asset.

Interest in banking, credit, or financial risk management.

What we offer:

Opportunity to contribute to real credit-risk decisioning at a Schedule I Canadian bank.

Direct mentorship from experienced risk and analytics professionals.

A role where strong quantitative work has immediate practical impact.

A professional environment that values clarity, rigour , and analytical thinking.

Application Procedure:

If working for a ‘non-traditional’ bank with an entrepreneurial flair appeals to you, we encourage you to apply. Please be advised that only those applicants selected for an interview will be contacted.

Apply Now

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