Join our Credit Eligibility team at M-KOPA

We're growing our Credit Eligibility team and looking for a Senior Analyst to help shape M-KOPA's credit risk and eligibility decisions for millions of people across Africa. Your analysis will directly influence who gets a loan, on what terms, and how we manage risk at scale - work that sits at the intersection of financial inclusion and rigorous data science.

The Impact

Your analysis will determine who gets access to credit - and for most of our customers, that access is transformational. We've already unlocked more than $2 billion in credit to over 7 million customers across five African markets. 55% of our customers are accessing a financial product for the first time through M-KOPA. 86% report an improvement in their quality of life. Every model you refine, every eligibility criterion you improve, contributes to that. It's your chance to be part of something that's literally transforming lives across an entire continent

The Opportunity

Mission-driven analytics: Your daily work - building underwriting frameworks, refining loan pricing, monitoring credit performance - directly determines who gets access to affordable credit across Kenya, Uganda, Nigeria, Ghana, and South Africa.

Global recognition: Join a company named by TIME 100 as one of the world's most influential and by the Financial Times as Africa's fastest-growing for four consecutive years (2022–2025).

Scale challenges: We process over 2 million payments daily and add 200,000 new customers every month. You'll be working with repayment data at a scale very few analysts ever encounter.

Environmental impact: We're carbon-negative, having avoided over 2.1 million tonnes of CO₂ emissions - and growing sustainably is core to how we operate.

What You'll Do

At M-KOPA, you'll own the analytical work that drives our lending strategy. Our Credit Eligibility team operates with a high degree of autonomy — you'll work cross-functionally with engineers, data scientists, growth managers, and commercial stakeholders across multiple countries, bringing analytical rigour to decisions that shape both credit performance and customer outcomes.

• Analyse M-KOPA's repayments data and other data sources to continuously improve credit scorecards and eligibility criteria while managing credit risk
• Refine loan pricing based on credit analysis and customer behaviour
• Test new loan types to understand customer demand and credit performance
• Monitor credit performance to detect risk shifts and quantify margin impact
• Test the predictiveness of new data sets for eligibility criteria purposes
• Use Python, SQL, and other tools to drive data insights
• Work with data scientists to leverage machine learning models as part of loan eligibility decisions

Your Technical Environment

• Languages & tools: Python, SQL, and other analytical tooling
• Data: Repayments data, customer behaviour data, third-party data sets
• Modelling: Risk modelling and statistical analysis across large, complex data sets
• Collaboration: Cross-functional work with engineers, data scientists, analysts, growth managers, and commercial stakeholders
• Context: Credit, underwriting, and lending analytics in emerging markets

Our Team Approach

• Low-ego, high-impact: We foster a collaborative environment where diversity, innovation, and rigour drive both commercial growth and social impact
• Data-driven decision-making: You'll be empowered to make the case for prioritisation and own the analysis that shapes lending strategy
• Ownership: You'll have a high degree of ownership over your domain - and the responsibility that comes with it
• Ambiguous problems welcome: We look for people who thrive when the problem isn't fully defined yet
• Newly established, fast-expanding: You'll be joining at a formative moment for our credit and underwriting capabilities

What You Need

We're looking for someone with experience in roles with significant analytical components who is ready to take real ownership of credit and eligibility decisions at scale.

Required experience:

• Strong statistical modelling and quantitative analysis skills, including the ability to conduct your own analysis of unstructured data