Credit Risk Data Scientist: Strategy & Insights

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

Job summary

TD is seeking a results-oriented analytics professional to support Retail Risk Management Credit Cards & Personal Lending. You will apply data, analytics, and stakeholder collaboration to solve business problems and drive meaningful outcomes across Product, Fraud, Technology, Operations, and Model Development.

You'll translate complex data into clear, actionable recommendations, design and monitor credit strategies, and influence decisions at senior levels while navigating ambiguity and

Qualifications

• Experience using data to influence business decisions and recommendations.
• Strong SQL skills and experience working with large, complex data sets.
• Exposure to Python, Databricks, Azure, predictive models, ML, or credit decisioning tools is an asset.

Responsibilities

• Own a portfolio, strategy, or business problem area end-to-end and become the trusted expert.
• Use data and analytics to identify opportunities and improve credit strategies and outcomes.
• Design, implement, monitor, and optimize credit strategies balancing growth, experience, profitability and risk.
• Influence decisions and build alignment across product, model development, fraud, tech, ops and leadership.
• Translate complex data into clear, actionable recommendations driving executive decisions.

Skills

SQL

Python

Databricks

Azure

Predictive models

Machine learning

Analytics

Education

Undergraduate degree in Mathematics/Statistics/Engineering/CS/Business Analytics

Graduate degree in a related field (asset)

Tools

Credit decisioning tools

AI-enabled productivity tools

Job description

TD is seeking a results-oriented analytics professional to support Retail Risk Management Credit Cards & Personal Lending. You will apply data, analytics, and stakeholder collaboration to solve business problems and drive meaningful outcomes across Product, Fraud, Technology, Operations, and Model Development.

You'll translate complex data into clear, actionable recommendations, design and monitor credit strategies, and influence decisions at senior levels while navigating ambiguity and