Jobless Developer

Intern - Credit Risk, Winter 2027

TorontoHybrid

AI Summary

Supports the development, monitoring, and optimization of credit adjudication and fraud prevention strategies by analyzing customer, operational, and portfolio data to generate insights, reports, and recommendations.

About this role

Join a Challenger

At EQ, we're remaking banking so every Canadian gets ahead, every day. Serving nearly 4 million Canadians from coast to coast, we offer a wide variety of financial services from banking and lending, to trust and credit union solutions.

We've been at this since 1970, challenging the conventions of traditional banking with smarter, faster, and more connected financial experiences.

What's kept us moving? The people behind it all: challengers who ask better questions, push back on old assumptions, and look for a better way forward.

If you're driven to help reshape how banking works for Canadians and the businesses that power our economy, this could be your next big opportunity.

We can’t wait to get to know you!


Work Term: January - April 2027
The Intern - Credit Risk Acquisitions supports the development, monitoring, and optimization of adjudication strategies across credit risk and fraud prevention. Through the analysis of customer, operational, and portfolio data, the Analyst generates insights, reporting, and recommendations that support strategy development, risk management, and business decision-making.

The Core Responsibilities of the Job

  • Analyze portfolio, operational, and customer data to identify trends, opportunities, and emerging risks across credit adjudication and fraud prevention
  • Develop, maintain, and enhance recurring management reporting, dashboards, KPI monitoring, and analytical tools to support risk governance and strategic decision-making.
  • Support the development and optimization of adjudication strategies by conducting quantitative analysis, monitoring performance, and evaluating potential improvements under the guidance of senior team members.
  • Perform data analysis and segmentation to evaluate customer behaviour, application outcomes, fraud trends, approval rates, loss performance, and operational effectiveness.
  • Assist in the design, testing, validation, and monitoring of adjudication strategy changes and enhancements within decisioning systems.
  • Produce ad hoc analysis and research to support strategic initiatives, business cases, forecasting activities, and management presentations.
  • Apply analytical techniques, statistical methods, and data visualization tools to generate actionable business insights.
  • Collaborate with partners across Credit Risk, Fraud, AML, Product, Marketing, and Operations to understand business requirements and support cross-functional initiatives.
  • Contribute to the continuous improvement of data assets, reporting processes, analytical methodologies, and decision-support tools.
  • Let's Talk About You!

  • Bachelor's degree in a quantitative discipline such as Statistics, Mathematics, Engineering, Computer Science, Data Science, Physics, Economics, or another STEM-related field.
  • 0 to 2 years of experience in data analytics, business analytics, risk analytics, financial services, consulting, or a related quantitative field. New graduates with strong technical and analytical capabilities are encouraged to apply.
  • Strong technical proficiency in SQL and Python, with demonstrated ability to manipulate, analyze, and interpret large datasets.
  • Strong analytical and problem-solving skills with the ability to translate data into meaningful insights and recommendations.
  • Excellent attention to detail and commitment to data quality and accuracy.
  • Effective written and verbal communication skills, with the ability to explain analytical findings to both technical and non-technical audiences.
  • Demonstrated ability to learn quickly, adapt to changing priorities, and work effectively in a fast-paced environment.
  • Experience with data visualization tools, cloud-based analytics platforms, machine learning, or statistical modelling is considered an asset.
  • Strong Microsoft Office skills, particularly Excel and PowerPoint.
  • Curiosity, initiative, and a willingness to develop expertise in credit risk, fraud prevention, customer acquisition, and financial services analytics.
  • How to Submit Your Application

  • In ONE document, please submit your transcript and resume. Failure to do so will result in your application not being considered.
  • Skills

    Cloud-based Analytics PlatformsDashboardsData SegmentationData VisualizationDecisioning SystemsExcelKPI MonitoringMachine LearningPowerPointPythonSQLStatistical MethodsStatistical Modelling

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