Credit & Fraud Analytics Intern (Winter 2027)

Location: Toronto, ON (Hybrid)

At Wealthsimple, we offer 4 to 8-month internships that are open to co-op and non-co-op students, and recent grads. During your internship, you will have the opportunity to contribute to projects that are changing the landscape of financial services for Canadians. You will be on a team that supports your growth, provides mentorship, and connects you to the broader Wealthsimple community!

Our internship program operates on a hybrid model out of our Toronto headquarters. You'll be in-office on Wednesdays and Thursdays to collaborate, connect, and learn in person, while maintaining the flexibility of remote work for the rest of the week.

About the Credit Analytics or Fraud Countermeasures team

This is a single posting for internship opportunities across two closely partnered risk teams. You'll be placed on one of them based on fit and business need, and you'll work with the other throughout your term.

Credit Analytics is part of Wealthsimple's retail lending group, building a team of exceptional lending professionals with diverse backgrounds. We're taking on green-field lending, starting with small data and growing through iteration and experimentation. The team manages a suite of inclusive retail lending products, optimizing risk and return while delighting customers. We're building inclusive financial products and want someone willing to challenge the status quo of what it means to be credit-worthy.

Fraud Countermeasures is responsible for enabling Wealthsimple to grow safely. We aim to balance fraud risk and client experience: our mission is to minimize losses while creating seamless experiences. Our goal is to use data and analytics to make every decision a rational one. The team is at the forefront of every new feature launch, and its strategies mitigate millions of dollars of attempted fraud annually while protecting the financial security of over 3 million clients.

Both roles require cross-functional collaboration with engineering, product, data science, and client experience teams. A typical week has you solving ambiguous problems in a fast-paced environment that prioritizes shipping and iterating new features for our clients. These teams are a great place to see your work deliver significant business impact and accelerate Wealthsimple's goal to be the primary financial service provider to millions of Canadians.

In this role, you'll have the opportunity to:

Depending on your placement, your projects will draw from the following:

Credit strategy and portfolio performance

• Support the development of strategies to manage risk and optimize performance across Wealthsimple's credit card products and other retail lending domains - approval, initial limits, line management, pricing, authorization, and collections.
• Evaluate the performance of lending portfolios, campaigns, strategies, and experiments.
• Recommend strategy enhancements to improve marginal profitability and mitigate emerging risks.
• Support the execution and analysis of retail lending campaigns that drive revenue by changing approvals, line management, pricing, credit limits, and recovery rates.

Fraud strategy and countermeasures

• Help build data-driven business cases around fraud strategies to manage risk on new and existing products, including our credit and prepaid card programs.
• Create metrics and visualizations to monitor account activity, applying judgment to uncover anomalous patterns.
• Apply financial modelling to estimate the fraud loss impact of new feature launches.
• Support the development of grounded decision thresholds using ML-based risk scores.

Shared across both

• Partner with data science, product, and engineering to bring ideas to market and implement strategies that drive immediate impact.
• Share trends and performance with leadership, and work across many teams to support roadmaps.

We're looking for someone who:

• Has strong data skills - dashboards, reporting, visualization, and data manipulation - with applied experience and demonstrated success in academic and/or professional settings.
• Has experience using SQL to conduct quantitative and qualitative analysis, and synthesizing results into actionable proposals.
• Can develop and communicate stories to both technical and non-technical stakeholders.
• Is able to internalize and weigh information to come to balanced decisions.
• Is intellectually curious, passionate about their work, and wants ownership over their projects.

The Interview Process

Applications close Sep 18th at 11:59 PM EST.

1. Application + Video Submission: Apply and upload a short video on the application form.

2. Technical Interview: A 1-hr coding interview with one or two interviewers. The interview will be conducted in SQL.

3. Final Interview: A 30 minute interview with two managers. Bring a project you're proud of and walk through your role, decisions, trade-offs, and lessons learned. We'll also discuss your collaboration style and how you approach learning and growth.

5. Offers: Offers extended!

Eligibility

• Enrolled in a Canadian post-secondary institution (in your third year of study or later) or a new graduate (Within 6 months of your graduation date)
• Available to work full-time hours
• Residing in Canada
• Able to commute to our Toronto HQ on Wednesdays and Thursdays

Nice-to-Have:

• Working toward a business or quantitative-based degree with high academic achievement.
• Any proven application of a coding language, with SQL and Python preferred.
• Exposure to statistical or quantitative analysis: experimental design, champion/challenger (or A/B) testing, model accuracy validation, constrained optimization, decision trees, discounted cash flows, and financial modelling.

Compensation & Equity

🤑 Base salary range: For this role, candidates can expect the following base salary range:
• Term 1 students: CAD $74,000 - $78,000
• Term 2 students: CAD $77,000 - $81,000
• Term 3 students: CAD $80,000 - $84,000
• Term 4 students: CAD $83,000 - $87,000
• Term 5 students: CAD $86,000 - $90,000

Your current year of study and number of past internship terms will determine your salary band. Actual compensation within each band is based on skills, experience, and academic performance. Exceptional candidates may be considered above the top of their year's range.