Lead predictive modeling at Canadian Tire Bank using machine learning, scorecards, and customer segmentation for credit lifecycle decisions.

As a Senior Data Scientist, you will develop and maintain models supporting acquisition, account management, and collections strategies. You will work with data scientists throughout model development and monitoring. The work emphasizes analytical rigor, regulatory soundness, and business impact across credit card customers.

Key Responsibilities:

- Lead machine learning projects for origination, limits, and collections
- Own scorecard planning, sourcing, modeling, and validation
- Deploy models and address scoring system issues
- Monitor model effectiveness and recommend appropriate actions




- Present model results and designs to senior management

Requirements:

- University degree in Statistics, Actuarial Science, or Mathematics
- Five or more years building predictive models and scorecards
- Proficiency in SQL, Python, and SAS programming languages
- Understanding of model development and modeling methodologies
- Ability to communicate analytical results to business stakeholders

Apply predictive modeling, scorecard development, and stakeholder communication to responsible credit decisions at Canadian Tire Bank.

📌 Senior Credit Risk Data Scientist (Oakville)
🏢 Canadian Tire Corporation
📍 Oakville