Data Scientist - Credit Eligibility at M-KOPA Nigeria

M-KOPA is a fast-growing FinTech company offering millions of underbanked customers across Africa access to life-enhancing products and services. From our roots as the pioneer in pay-as-you-go “PayGo’” solar energy for off grid homes, we have grown into one of the most advanced connected asset financing platforms in the world, empowering a broad range of customers to achieve progress in their lives.

We are recruiting to fill the position below:

Job Title: Data Scientist - Credit Eligibility

Location: Lagos

Description

• We're looking for a Data Scientist who loves building predictive models and solving ambiguous data problems.
• You'll own the models that shape loan eligibility and pricing across 5 African markets.
• This is a small team with big responsibility, where your work directly shapes lending strategy for millions of customers.

The Impact

• Your models will directly shape how millions of underserved customers access credit for the first time.
• We've already helped over 7 million customers access over $2 billion in credit - and we process over 1.5 million payments daily. It's your chance to be part of something that's literally transforming lives across an entire continent.

The Opportunity

• Mission-driven data science: Build credit scoring and pricing models that expand financial access for customers traditionally excluded from formal lending
• 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 4 consecutive years (2022–2025)
• Scale challenges: Work with rich repayment datasets across 5 African markets, developing ML models that balance growth with credit risk at scale
• Environmental impact: We're carbon-negative, having displaced over 2.1 million tonnes of emissions.

What You'll Do

• At M-KOPA, you'll build and refine the predictive models that power our lending strategy.
• You'll sit within a small, high-performing team with end-to-end ownership of credit scoring, loan eligibility, and pricing optimisation — working cross-functionally with engineers, analysts, growth managers, and commercial stakeholders across multiple countries.
• Join us in combining cutting-edge data science with purpose-driven work that makes digital and financial inclusion possible across Africa.

Day to day, you'll be:

• Building and refining credit scoring models that assess customer creditworthiness, default risk, and loan pricing across multiple markets
• Developing and testing ML models for loan eligibility and pricing optimisation through A/B testing and statistical analysis
• Continuously improving eligibility criteria by analysing repayment data, engineering new features, and monitoring credit performance for risk shifts and margin impact
• Collaborating cross-functionally with engineers, data scientists, and commercial stakeholders to scale models into production.

Technical Environment:

• Languages & Libraries: Python, SQL, scikit-learn, pandas, numpy, and relevant ML libraries
• Techniques: Predictive modelling, classification/regression, feature engineering, model selection, hyperparameter tuning, A/B testing
• Domain: Credit scoring, underwriting, loan pricing, risk analytics.

Our Team Approach:

• Low-ego environment where diversity, innovation, and collaboration drive both commercial growth and social impact
• High degree of ownership over your domain — you're empowered to make data-driven decisions and prioritise solutions
• Cross-functional collaboration with engineering, product, and commercial teams across multiple countries
• Analytical rigour combined with deep market understanding to serve customers excluded from formal financial services

What You Need

• Credit accessibility and affordability are at the core of this role.
• You'll join a small, high-performing team where every day brings new modelling challenges and analyses that shape our lending strategy.
• If building models that can transform financial access for millions of African customers excites you, we'd love to hear from you.

Required Experience:

• Experience building predictive models, particularly credit scoring, risk models, or similar classification/regression problems
• ML background with hands-on experience in model development, validation, deployment, and performance monitoring
• Proficiency in Python, SQL, and relevant ML libraries (scikit-learn, pandas, numpy, etc.) with experience in feature engineering, model selection, and hyperparameter tuning
• Experience translating complex model outputs into actionable business strategies and stakeholder communications
• Ability to work cross-functionally with product, engineering, and commercial teams
• Strong data communication skills — written, oral, and visual.

Highly Desirable:

• Experience in credit, underwriting, lending analytics, or fintech modelling.

Application Closing Date
Not Specified.

How to Apply
Interested and qualified candidates should:
Click here to apply online