Data Scientist - Credit Eligibility

We are looking for a Data Scientist who loves building predictive models and solving ambiguous data problems. You will 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.

Impact

• Your models will directly shape how millions of underserved customers access credit for the first time.
• We have already helped over 7 million customers access over $2 billion in credit - and we process over 1.5 million payments daily.

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 are carbon-negative, having displaced over 2.1 million tonnes of emissions.

What You’ll Do

At M-KOPA, you will build and refine the predictive models that power our lending strategy. You will 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.

Day to day, you will 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 are 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 will 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 would 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.

Location & Benefits

• Fully remote role within UTC -1 to UTC +3 time zones.
• Work with diverse teams across UK, Europe, and Africa.
• Professional development programmes and coaching partnerships.
• Family-friendly policies and flexible working arrangements.
• Well-being support and career growth opportunities.

Our Mission

We make financing for everyday essentials accessible to everyone. We strive to drive greater inclusion of women, youth, and low-income communities.

Our Impact

• Connected: 2.5 million first-time smartphone users connected.
• Prosperous: 70% of customers use M-KOPA products for income generation, with 35,000 livelihoods created for agents.
• Green: 2.1 million tonnes of CO₂ avoided through clean energy products, with over 127,700 circular economy products provided.

Ready to build models that create real-world financial inclusion while advancing your career in data science? 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, prioritise well-being, and embrace flexibility. Join us in shaping the future of M-KOPA as we grow together.

Recognised four times by the Financial Times as one of Africa's fastest growing companies (2022, 2023, 2024 and 2025) and by TIME100 Most influential companies in the world 2023 and 2024, we have 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 or charge any money as a pre-employment or post-employment requirement. This means 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.