
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.

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.

๐ Apply your skills to new domain: Use customer behaviour analytics you already know to solve credit risk - we'll teach you the credit concepts
๐ Massive scale & impact: 3 million active customers, 200,000 new customers monthly, 1.5 million daily payments to analyse
๐งช Experimentation culture: Constantly test credit policies through A/B tests and causal inference - measure what works
๐ Mission-driven FinTech: TIME 100 company driving financial inclusion across Africa (Financial Times' fastest-growing company 2022-2025)
๐ Real impact: 70% of customers use M-KOPA products for income generation | 2.5 million first-time internet users connected
Credit Analytics
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
Experimentation & Optimisation
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
Strategic Analytics & Insights
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
Technical Execution
Build automated dashboards and reporting
Develop data pipelines for credit decisioning
Ensure model performance monitoring and validation
What We're Looking For
Quantitative Academic Foundation
Bachelor's degree in Statistics, Actuarial Science, Economics, Mathematics, Econometrics, or another quantitative field
Customer Behaviour Analytics (4+ years)
Experience analysing customer/user behaviour patterns using data
Built predictive models for business decisions (churn, retention, conversion, segmentation)
Understanding of customer lifecycle, behavioural triggers, and pattern recognition
Predictive Modeling & ML
Built classification/regression models that influenced business decisions
Experience with model evaluation, feature engineering, and deployment
Not just academic knowledge - actual production models that drove outcomes
Technical Skills
Python OR R for data analysis and modeling (pandas, scikit-learn, statsmodels, tidyverse, caret)
SQL for data extraction and analysis (joins, CTEs, window functions)
Experience building models, not just running queries
Experimentation & Hypothesis Testing
Designed or analysed A/B tests, randomised experiments, or causal inference studies
Understanding of statistical rigour, test design, and measuring impact
Nice-to-Haves
Business Intelligence tools: Power BI, Tableau, Looker
Africa/Emerging markets experience: Understanding of thin-file lending, financial inclusion, or emerging market dynamics
Credit/Fintech exposure: Any experience with lending, credit, fintech, mobile money, or payments (bonus but not required)
Executive communication: Experience presenting to senior leadership or translating analytics into strategic recommendations
What Makes You Stand Out
We would love to hear from you if:
You've predicted customer churn and can see how that transfers to default prediction
You've built segmentation models and understand they're similar to risk segmentation
You design experiments to test hypotheses, not just build dashboards
You translate complex analytics into clear recommendations for executives
You're excited to learn credit concepts while applying analytical skills you already have
The Credit Risk & Analytics team manages credit risk, portfolio performance, and data-driven decision-making across M-KOPA's consumer finance products. They are an established but evolving team, scaling their capabilities as the business grows in complexity and reach. Working closely with Product, Finance, and Operations, they play a central role in shaping credit strategy and performance at scale.

Professional development programs and coaching partnerships
Family-friendly policies and flexible working arrangements
Well-being support and career growth opportunities
Hybrid working in Ghana with diverse teams across UK, Europe, and Africa
Apply now!
At M-KOPA, we empower our people to ow
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