Analyst, Credit Risk

Go Fractional; Toronto; Hybrid; CAD 65,000 - 90,000; Full time

Job summary

Go Fractional is seeking an Analyst, Credit Risk for a hybrid role in Toronto. The position will support development and optimization of adjudication strategies across credit risk and fraud prevention, using data-driven insights to inform strategy and governance.

The candidate will analyze portfolio and customer data, develop dashboards, and collaborate with Credit Risk, Fraud, AML, Product, Marketing and Operations to drive risk-informed decisions in a fast-paced environment.

Qualifications

• Bachelor’s degree in a quantitative field.
• 0–2 years in data analytics or risk analytics.
• Strong SQL and Python skills.
• Ability to translate data into insights and recommendations.
• Attention to data quality and accuracy.
• Clear written and verbal communication.
• Able to learn quickly in a fast-paced environment.

Responsibilities

• Analyze portfolio, operations, and customer data to identify risks and trends.
• Develop dashboards, KPI monitoring, and reporting for risk governance.
• Support adjudication strategy improvements via quantitative analysis.
• Perform data segmentation to evaluate behavior, outcomes, and fraud trends.
• Assist in designing, testing, and monitoring adjudication strategy changes.
• Produce ad hoc analyses for strategic initiatives and forecasts.
• Apply statistical methods to generate actionable business insights.
• Collaborate with Credit Risk, Fraud, AML, Product, Marketing and Ops.

Skills

SQL

Python

Data analytics

Communication

Attention to detail

Problem solving

Education

Quantitative degree

Tools

Excel

PowerPoint

Data visualization

Cloud analytics

Job description

Analyst, Credit Risk (18 Month Contract)

Location: Toronto
Work Arrangement: Hybrid
Contract Duration: 18 months

The Work

The Analyst, Credit Risk Acquisitions supports the development, monitoring, and optimization of adjudication strategies across credit risk and fraud prevention. Through the analysis of customer, operational, and portfolio data, the Analyst generates insights, reporting, and recommendations that support strategy development, risk management, and business decision-making.

Core Responsibilities

• Analyze portfolio, operational, and customer data to identify trends, opportunities, and emerging risks across credit adjudication and fraud prevention

• Develop, maintain, and enhance recurring management reporting, dashboards, KPI monitoring, and analytical tools to support risk governance and strategic decision-making.

• Support the development and optimization of adjudication strategies by conducting quantitative analysis, monitoring performance, and evaluating potential improvements under the guidance of senior team members.

• Perform data analysis and segmentation to evaluate customer behaviour, application outcomes, fraud trends, approval rates, loss performance, and operational effectiveness.

• Assist in the design, testing, validation, and monitoring of adjudication strategy changes and enhancements within decisioning systems.

• Produce ad hoc analysis and research to support strategic initiatives, business cases, forecasting activities, and management presentations.

• Apply analytical techniques, statistical methods, and data visualization tools to generate actionable business insights.

• Collaborate with partners across Credit Risk, Fraud, AML, Product, Marketing, and Operations to understand business requirements and support cross-functional initiatives.

• Contribute to the continuous improvement of data assets, reporting processes, analytical methodologies, and decision-support tools.

Qualifications

• Bachelor's degree in a quantitative discipline such as Statistics, Mathematics, Engineering, Computer Science, Data Science, Physics, Economics, or another STEM-related field.

• 0 to 2 years of experience in data analytics, business analytics, risk analytics, financial services, consulting, or a related quantitative field. New graduates with strong technical and analytical capabilities are encouraged to apply.

• Strong technical proficiency in SQL and Python, with demonstrated ability to manipulate, analyze, and interpret large datasets.

• Strong analytical and problem-solving skills with the 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, with the ability to explain analytical findings to both technical and non-technical audiences.

• Demonstrated ability to learn quickly, adapt to changing priorities, and work effectively in a fast-paced environment.

Preferred Skills

• Experience with data visualization tools, cloud-based analytics platforms, machine learning, or statistical modelling

• 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

Work Location

The incumbent will be working hybrid with in-office time spent at EQ Bank's office located at 2200-25 Ontario Street, Toronto, ON.