Senior Risk Analyst (Analytics)
Role Overview
The Senior Risk Analyst joins goeasy's Risk and Analytics team and reports to the Senior Manager, Risk and Analytics.
The role supports credit risk management, portfolio monitoring, risk strategies, analytics, controls, and data-driven decisions for profitable growth.
The analyst provides insights to business partners and works cross-functionally as business and data needs evolve.
Key Skills for This Role
Full Job Posting
Role overview
The Senior Risk Analyst joins goeasy's Risk and Analytics team and reports to the Senior Manager, Risk and Analytics.
The role supports credit risk management, portfolio monitoring, risk strategies, analytics, controls, and data-driven decisions for profitable growth.
The analyst provides insights to business partners and works cross-functionally as business and data needs evolve.
Data mining, modeling and analysis
- Investigate, document, and report drivers of unexpected portfolio or origination changes and credit performance across retail, online, and alternative lending channels.
- Support development of risk models for origination, account management, and collections.
- Analyze credit strategy optimization, including customer risk segmentation to improve portfolio risk-reward.
- Forecast and measure loss rates, approval rates, loan conversion rates, and credit quality for initiatives and marketing campaigns.
Forecasting and reporting
- Maintain standard reports evaluating overall credit risk of the portfolio.
- Monitor delinquency and charge-off trends by vintage and segment, apply observations to loss forecasts, and communicate forecast risks and opportunities to senior management.
- Analyze the effects of external factors and policy or operational changes on delinquency and charge-off levels.
- Monitor key risk indicators and conduct periodic credit reviews to assess portfolio and business-unit risk and performance.
Experience and qualifications
- Requires at least two years of experience as an analyst or in a similar position.
- Requires strong knowledge of quantitative methodologies, risk models, statistical analysis, and modeling techniques.
- Requires a university degree in Statistics, Mathematics, or a related discipline; an advanced degree is desired.
- Requires a solid understanding of data extraction, mining, and modeling tools, including SAS and SQL.
- Requires strong analytical problem-solving, clear communication, adaptability, and ability to manage competing demands and tight timelines.
Work arrangement
- The flexible work program requires three days onsite per week at the Mississauga office.
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