Join our Credit & Underwriting team!
We're looking for a Senior Data Scientist who loves building machine learning models and solving ambiguous data problems. This is a fully remote data science role within a growing mission-driven fintech. 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
What You'll Do
At M-KOPA, you'll build and refine the machine learning and credit risk 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:
Technical Environment 💻
Our Team Approach
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:
Highly Desirable:
Location & Benefits
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:
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.
_