Data Analyst - Credit

Kuda, which means ‘love’ in Shona, is more than a fintech - it’s a movement to make financial services accessible, affordable, and truly rewarding for every African. Backed by over $100 million from some of the world’s most respected investors, we’re building a smarter alternative to traditional banking - offering seamless money transfers, business banking, and instant access to credit, all through your device. At Kuda, we don’t just build products - we build people. We share the love in how we collaborate, carry everyone along as we grow, break boundaries to challenge what’s possible, and show up every day committed to doing better. If you’re driven by purpose, excited by impact, and ready to help redefine the future of finance in Africa, you’ll feel right at home here. 

Role Overview 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: Annualised loss Vintage curves Roll rates Exposure at Default (EAD) Loss Given Default (LGD)