Business Data Analyst

Join one of Canada’s fastest-growing companies and be part of something extraordinary - welcome to **goeasy** At **goeasy**, our people and culture are at the heart of everything we do, and we’re proud to be recognized for it. We’ve earned prestigious accolades such as **Waterstone Canada’s Most Admired Corporate Cultures**, **Canada’s Top Growing Companies**, and the **TSX30**, highlighting us as one of **the top performers on the TSX**. We’re also thrilled to be named a **Greater Toronto Top Employer** and proudly certified as a **Great Place to Work®.** These honors reflect our commitment to fostering an inclusive, high-performance culture where talent thrives and innovation drives us forward.

As one of Canada’s leading alternative consumer lenders, we’re passionate about helping everyday Canadians create a brighter future. Our vision is to provide a path to a better tomorrow, today. We offer a full range of products, including non-prime leasing, unsecured and secured loans, and point-of-sale financing through **easyhome**, **easyfinancial**, and **LendCare**. If you're seeking an exciting, high-growth environment where your contributions truly matter, we want to hear from you Join us, and together, let's create a future of financial empowerment.

**What will you be doing?**

**Problem Solving, Data Analysis & Strategic Optimization**
- Identify key issues and opportunities within the credit card portfolio by analyzing large datasets and financial metrics.
- Propose data-driven solutions and strategies to optimize portfolio performance, reduce risk, and improve customer retention.
- Leverage advanced data science techniques, including machine learning and predictive modeling, to uncover insights that drive strategic decisions.
- Develop and test strategies to enhance portfolio profitability and customer experience, ensuring alignment with business objectives.
- Work with stakeholders to identify areas for portfolio optimization, such as product enhancements, pricing strategies, and customer segmentation.

**Collaboration, Communication & Recommendations**
- Collaborate with internal teams, including marketing, product management, and risk, to implement strategies that improve portfolio performance.
- Partner with data scientists and business analysts to integrate advanced analytics and improve decision-making across the organization.
- Develop and present clear, data-driven recommendations to senior leadership and other key stakeholders.
- Effectively communicate complex analytical findings in a concise and actionable manner, ensuring alignment across teams.

**Model Development, Testing & Fraud Mitigation**
- Build and test predictive models that forecast portfolio performance, customer behavior, and emerging risks.
- Continuously evaluate and refine models to ensure they provide accurate and actionable insights.
- Work closely with the risk management team to develop and implement strategies that minimize portfolio risk while maximizing profitability.

**Continuous Learning, Innovation & Documentation**
- Stay ahead of industry trends and emerging technologies, incorporating innovative approaches to data analysis and modeling.
- Promote a culture of continuous learning by taking on new challenges and responsibilities, while contributing to the team’s growth and knowledge-sharing efforts.
- Document business requirements, analytical methodologies, and model assumptions to ensure clarity and transparency in decision-making processes.
- Streamline reporting processes and develop efficient workflows for ongoing portfolio monitoring.

**Project Management & Implementation**
- Lead cross-functional teams through the entire problem-solving lifecycle—from framing business problems, testing hypotheses, and analyzing data, to solution development and implementation.
- Develop operational feasibility plans and ensure successful project execution, while monitoring outcomes and adjusting strategies as necessary.

**What experience do you have?**
- Bachelor’s degree in Data Science, Mathematics, Computer Science, Economics, or a related field. Relevant certifications (e.g., Machine Learning, Data Science) are a plus.
- Minimum of 3 years of experience as a Senior Analyst or in a similar analytical role, preferably within the financial services or credit card industry.
- Proven experience in building and testing predictive models, analyzing financial portfolios, and recommending data-driven strategies.
- Familiarity with credit card products, customer behavior analysis, and key industry metrics (e.g., delinquency rates, APR, charge-offs, utilization).
- Expertise in data science tools and programming languages (e.g., Python, R, SQL) and machine learning libraries (e.g., scikit-learn, TensorFlow).
- Strong ability to perform statistical analysis and data visualization, with experience using tools like Tableau, Power BI, or similar platforms.
- Excellent communication skills, with the ability to present complex tech