‹ Back
Senior Analytics Manager - Customer Behaviour
JOB SUMMARY
Roles
Job details
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 connectedThe RoleCredit AnalyticsBuild credit scoring models using alternative data - mobile money patterns, transactional behaviour, payment consistency signalsDevelop risk segmentation and customer profiling frameworksMonitor portfolio performance and identify early warning signalsTranslate customer behaviour patterns into credit risk indicatorsExperimentation OptimisationDesign A/B tests to evaluate credit policy changes (loan amounts, terms, pricing, approval thresholds)Analyse experiment results to optimise approval rates, default rates, and profitabilityRun cohort analyses and measure incrementality of interventionsStrategic Analytics InsightsPresent findings to executives and credit committeesDevelop strategic recommendations based on data analysisCollaborate cross-functionally with Product, Risk, Operations, FinanceBuild business cases for credit policy changes
Technical
ExecutionBuild automated dashboards and reportingDevelop data pipelines for credit decisioningEnsure model performance monitoring and validationWhat We're Looking ForQuantitative Academic FoundationBachelor's degree in Statistics, Actuarial Science, Economics, Mathematics, Econometrics, or another quantitative fieldCustomer Behaviour Analytics (4+ years)Experience analysing customer/user behaviour patterns using dataBuilt predictive models for business decisions (churn, retention, conversion, segmentation)Understanding of customer lifecycle, behavioural triggers, and pattern recognitionPredictive Modeling ML (3+ years hands-on)Built classification/regression models that influenced business decisionsExperience with model evaluation, feature engineering, and deploymentNot just academic knowledge - actual production models that drove outcomes
Technical
SkillsPython 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 queriesExperimentation Hypothesis TestingDesigned or analysed A/B tests, randomised experiments, or causal inference studiesUnderstanding of statistical rigour, test design, and measuring impactNice-to-HavesBusiness Intelligence tools: Power BI, Tableau, LookerAfrica/Emerging markets experience: Understanding of thin-file lending, financial inclusion, or emerging market dynamicsCredit/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 recommendationsWhat Makes You Stand OutWe would love to hear from you if:You've predicted customer churn and can see how that transfers to default predictionYou've built segmentation models and understand they're similar to risk segmentationYou design experiments to test hypotheses, not just build dashboardsYou translate complex analytics into clear recommendations for executivesYou're excited to learn credit concepts while applying analytical skills you already haveThe TeamThe 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 partnershipsFamily-friendly policies and flexible working arrangementsWell-being support and career growth opportunitiesHybrid working in Ghana with diverse teams across UK, Europe, and AfricaReady 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 NoticeM-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.
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 connectedThe RoleCredit AnalyticsBuild credit scoring models using alternative data - mobile money patterns, transactional behaviour, payment consistency signalsDevelop risk segmentation and customer profiling frameworksMonitor portfolio performance and identify early warning signalsTranslate customer behaviour patterns into credit risk indicatorsExperimentation OptimisationDesign A/B tests to evaluate credit policy changes (loan amounts, terms, pricing, approval thresholds)Analyse experiment results to optimise approval rates, default rates, and profitabilityRun cohort analyses and measure incrementality of interventionsStrategic Analytics InsightsPresent findings to executives and credit committeesDevelop strategic recommendations based on data analysisCollaborate cross-functionally with Product, Risk, Operations, FinanceBuild business cases for credit policy changes
Technical
ExecutionBuild automated dashboards and reportingDevelop data pipelines for credit decisioningEnsure model performance monitoring and validationWhat We're Looking ForQuantitative Academic FoundationBachelor's degree in Statistics, Actuarial Science, Economics, Mathematics, Econometrics, or another quantitative fieldCustomer Behaviour Analytics (4+ years)Experience analysing customer/user behaviour patterns using dataBuilt predictive models for business decisions (churn, retention, conversion, segmentation)Understanding of customer lifecycle, behavioural triggers, and pattern recognitionPredictive Modeling ML (3+ years hands-on)Built classification/regression models that influenced business decisionsExperience with model evaluation, feature engineering, and deploymentNot just academic knowledge - actual production models that drove outcomes
Technical
SkillsPython 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 queriesExperimentation Hypothesis TestingDesigned or analysed A/B tests, randomised experiments, or causal inference studiesUnderstanding of statistical rigour, test design, and measuring impactNice-to-HavesBusiness Intelligence tools: Power BI, Tableau, LookerAfrica/Emerging markets experience: Understanding of thin-file lending, financial inclusion, or emerging market dynamicsCredit/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 recommendationsWhat Makes You Stand OutWe would love to hear from you if:You've predicted customer churn and can see how that transfers to default predictionYou've built segmentation models and understand they're similar to risk segmentationYou design experiments to test hypotheses, not just build dashboardsYou translate complex analytics into clear recommendations for executivesYou're excited to learn credit concepts while applying analytical skills you already haveThe TeamThe 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 partnershipsFamily-friendly policies and flexible working arrangementsWell-being support and career growth opportunitiesHybrid working in Ghana with diverse teams across UK, Europe, and AfricaReady 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 NoticeM-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.
Discover the company
Explore other offers from this company or learn more about M-KOPA.
The company
M
M-KOPA Ghana
