Senior Analytics Manager - Customer Behaviour

We're hiring a Senior Analytics Manager for our team in Ghana. If you've spent years building predictive models to understand customer behaviour - we want to teach you how to apply that exact thinking to credit decisions. Your models will unlock financial inclusion for millions across Africa. Here's our philosophy: We can teach credit domain knowledge. We cannot teach analytical rigour. The Impact 💚 Most of our 7 million customers have no traditional credit history. Yet we've unlocked over $2 billion in credit. Your challenge will be to build predictive models using alternative data to determine who gets their first smartphone, their first formal loan, their first real opportunity to build financial security. Then design experiments to continuously improve those decisions. The Opportunity 📊 Apply your skills to new domain: Use customer behaviour analytics you already know to solve credit risk - we'll teach you the credit concepts 🚀 Massive scale & impact: 3 million active customers, 200,000 new customers monthly, 1.5 million daily payments to analyse 🧪 Experimentation culture: Constantly test credit policies through A/B tests and causal inference - measure what works 🚀 Mission-driven FinTech: TIME 100 company driving financial inclusion across Africa (Financial Times' fastest-growing company 2022-2025) 🌍 Real impact: 70% of customers use M-KOPA products for income generation | 2.5 million first-time internet users connected The Role Build credit scoring models using alternative data - mobile money patterns, transactional behaviour, payment consistency signals Develop risk segmentation and customer profiling frameworks Monitor portfolio performance and identify early warning signals Translate customer behaviour patterns into credit risk indicators Design A/B tests to evaluate credit policy changes (loan amounts, terms, pricing, approval thresholds) Analyse experiment results to optimise approval rates, default rates, and profitability Run cohort analyses and measure incrementality of interventions Present findings to executives and credit committees Develop strategic recommendations based on data analysis Collaborate cross-functionally with Product, Risk, Operations, Finance Build business cases for credit policy changes Build automated dashboards and reporting Develop data pipelines for credit decisioning Ensure model performance monitoring and validation