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About the Role
The Analyst, Credit Risk Scoring supports the development, monitoring, validation, and optimization of credit risk, fraud, and account management scorecards. This role generates insights and recommendations supporting scorecard strategy, model governance, risk management, and business decision-making, offering exposure to predictive analytics, credit scoring, machine learning, and decision science in financial services.
Responsibilities
- Analyze customer, portfolio, bureau, and scorecard performance data to identify trends, opportunities, and risk signals.
- Support the development, monitoring, recalibration, and optimization of scorecards and alternative risk frameworks.
- Produce recurring score monitoring reports and dashboards.
- Monitor model and scorecard performance using industry-standard metrics.
- Support the investigation of score performance shifts, model drift, data anomalies, and emerging portfolio trends.
- Develop and maintain SQL queries, analytical datasets, automated reporting solutions, and dashboards.
- Apply statistical techniques, machine learning concepts, and data visualization tools to generate actionable business insights.
- Prepare presentations and analytical summaries for reviews and discussions.
- Collaborate with stakeholders across Credit Risk, Fraud, AML, Product, Marketing, Technology, and Model Risk Management.
- Contribute to continuous improvement initiatives for model monitoring, reporting automation, data quality, and analytical processes.
Requirements
- Bachelor's degree in a quantitative discipline (Statistics, Mathematics, Engineering, Computer Science, Data Science, Physics, Economics, or other STEM-related field).
- 0 to 5 years of experience in data analytics, business analytics, risk analytics, financial services, consulting, or a related quantitative field.
- Strong technical proficiency in SQL and Python.
- Demonstrated ability to manipulate, analyze, and interpret large datasets.
- Strong analytical and problem-solving skills.
- 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.
- Ability to explain analytical findings to technical and non-technical audiences.
- Demonstrated ability to learn quickly, adapt to changing priorities, and work effectively in a fast-paced environment.
- 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.
- Experience with data visualization tools, cloud-based analytics platforms, machine learning, or statistical modelling is considered an asset.
- Must successfully complete a criminal background check and credit check.
Skills
- SQL
- Python
- Data manipulation
- Data analysis
- Data interpretation
- Statistical techniques
- Machine learning concepts
- Data visualization
- Microsoft Excel
- Microsoft PowerPoint
Location
- Toronto, ON
Work Type
- Hybrid
Experience Level
- 0-5 years
- New graduates encouraged
Education Level
- Bachelor's degree in a quantitative discipline
Benefits
- Competitive discretionary bonus
- Market leading RRSP match program
- Medical, dental, vision, life, and disability benefits
- Employee Share Purchase Plan
- Maternity/Parental top-up
- Generous vacation policy and personal days
- Professional development and comprehensive Career Development program
About the Company
- EQ is remaking banking so every Canadian gets ahead, every day.
- Serving nearly 4 million Canadians from coast to coast, offering a wide variety of financial services.
- Challenging the conventions of traditional banking with smarter, faster, and more connected financial experiences since 1970.
- EQB Inc. is the parent company of Equitable Bank, Canada's Challenger Bank™.
- EQB Inc. manages approximately $150 billion in combined assets under management and administration.
Equal Opportunity
- EQ is committed to building an inclusive, accessible environment where every employee feels valued, respected, and supported.
- Honouring and celebrating diverse experiences, identities, and perspectives.
- Providing a barrier-free recruitment process and work environment.
- Offering accommodations at any stage of the recruitment process.
- AI is used to help screen, assess, and/or select applicants, with AI-enabled outputs reviewed and validated by the talent team.