As a Data Analyst - Credit, you are supporting the analytics throughout the credit product life cycle, from product design, to credit acquisition, portfolio management, collection and profit & loss.
You will work within the Decision Science team, reporting to the Credit Risk Analytics Lead.
Key Responsibilities
Analyze portfolio performance metrics to identify trends, risks, and opportunities
Review and refine credit policies, including rule-based decision engines
Build and maintain profit and loss forecasts to guide strategic decisions
Conduct credit limit assignment and affordability assessments
Perform score cut-off analysis to improve approval and risk strategies
Monitor and enhance collection strategies based on customer segmentation and outcomes
Design and run A/B tests to assess and optimize lending and collections performance
Communicate actionable insights and recommendations to senior stakeholders
Requirements
Academic background in a mathematical discipline (e.g. Mathematics, Statistics, Physics, or related field)
Minimum of 3 years' experience as a Quantitative Analyst or Data Analyst in a financial services, fintech or e-commerce environment
Strong proficiency in SQL for data extraction and manipulation
Hands-on experience with open-source statistical programming languages such as Python or R
Solid understanding of statistical tests commonly used in A/B testing
Experience using statistical software packages (open-source preferred)
Proven experience developing and maintaining analytical reports or dashboards from end-to-end
Ability to interpret and present insights from reports in a business context, including stakeholder engagement and recommendation
Bonus Points:
Strong understanding of credit risk and portfolio performance metrics, including: