We're looking for a Senior 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
Strong 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
Our technology has created measurable change:
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, 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.