Credit Risk Data Scientist — Strategy & Insights Lead

TD; Toronto; On-site; CAD 82,000 - 115,000; Full time

Job summary

TD is seeking a results-driven analytics professional to support risk credit card portfolios in Toronto. You will blend analytics, strategy, and stakeholder collaboration to solve complex business problems and drive meaningful outcomes.

You will work with Product, Fraud, Technology, and Operations to shape credit strategies, improve customer outcomes, and balance growth with risk. Strong SQL, data storytelling, and collaboration are essential.

Qualifications

• Experience solving business problems with data and analytics.
• Ability to translate analysis into clear recommendations.
• Strong SQL skills with large data sets.
• Exposure to Python/Databricks/Azure is a plus.
• Attention to detail and healthy skepticism.

Responsibilities

• Own a portfolio or business area end-to-end and act as trusted expert.
• Use data and analytics to identify opportunities and improve outcomes.
• Design, implement, monitor, and optimize credit strategies balancing growth and risk.
• Influence decisions and align across product, risk, fraud, and technology teams.
• Translate complex data into clear, actionable recommendations for execs.
• Monitor portfolio performance and identify emerging risks and opportunities.
• Leverage analytics and AI tools to improve efficiency and insights.

Skills

SQL

Data analytics

Stakeholder engagement

Credit risk understanding

Problem solving

Education

Bachelor's degree in a quantitative field

Graduate degree (asset)

Tools

Python

Databricks

Azure

Predictive models

Job description

TD is seeking a results-driven analytics professional to support risk credit card portfolios in Toronto. You will blend analytics, strategy, and stakeholder collaboration to solve complex business problems and drive meaningful outcomes.

You will work with Product, Fraud, Technology, and Operations to shape credit strategies, improve customer outcomes, and balance growth with risk. Strong SQL, data storytelling, and collaboration are essential.