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Credit & Fraud Analytics Intern (Winter 2027)

Wealthsimple Toronto, OntarioUSD 74,000–78,000 / yearInternship

Key requirements

  • Python
  • Sql
  • Data Science
  • Financial Modelling
  • Security
Build something people love Wealthsimple is Canada’s leading financial innovator. The company offers a full suite of simple, sophisticated financial products across managed investing, do-it-yourself trading, cryptocurrency, tax filing, spending and saving. Wealthsimple currently serves more than 4 million Canadians and holds over $155 billion in assets under administration. The company was founded in 2014 by a team of financial experts and technology entrepreneurs, and is headquartered in Toronto, Canada. We're proud of what we've built — and we're just getting started. Read our Culture Manual and learn more about how we work . Internships @ Wealthsimple 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 m

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