Job Description
We’re hiring a Senior Analytics Manager for our team in Ghana. If you’ve spent years building predictive models to understand customer behaviour (churn, retention, conversion, lifecycle) - 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 (churn prediction, segmentation, A/B testing) 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
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 (3+ years hands-on)
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 Team
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.
Benefits
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
Ready to drive responsible financial inclusion through world-class credit analytics?
Apply now!
Why M-KOPA?
At M-KOPA, we empower our people to own their careers through diverse development programs, coaching partnerships, and on-the-job training. We support individual journeys with family-friendly policies, prioritize well-being, and embrace flexibility.
Join us in shaping the future of M-KOPA as we grow together. Explore more at m-kopa.com.
Recognized four times by the Financial Times as one Africa’s fastest growing companies (2022, 2023, 2024 and 2025) and by TIME100 Most influential companies in the world 2023 and 2024 , we’ve served over 6 million customers, unlocking $1.5 billion in cumulative credit for the unbanked across Africa.
Important Notice
M-KOPA is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained staff. Women, minorities, and people with disabilities are strongly encouraged to apply.
M-KOPA explicitly prohibits the use of Forced or Child Labour and respects the rights of its employees to agree to terms and conditions of employment voluntarily, without coercion, and freely terminate their employment on appropriate notice. M-KOPA shall ensure that its Employees are of legal working age and shall comply with local laws for youth employment or student work, such as internships or apprenticeships.
M-KOPA does not collect/charge any money as a pre-employment or post-employment requirement. This means that we never ask for ‘recruitment fees’, ‘processing fees’, ‘interview fees’, or any other kind of money in exchange for offer letters or interviews at any time during the hiring process.
Applications for this position will be reviewed on a rolling basis. Shortlisting and interviews will take place at any stage during the recruitment process. We reserve the right to close the vacancy early if a suitable candidate is selected before the advertised closing date.
If your application is successful M-KOPA undertakes pre-employment background checks as part of its recruitment process, these include; criminal records, identification verification, academic qualifications, employment dates and employer references.
