About Us

We’re building the future of financial inclusion, and data-driven decision making is at the heart of our mission. Our team combines analytical rigor with deep market understanding to develop loan eligibility and pricing for customers who have traditionally been excluded from formal financial services.

We foster a low-ego environment where diversity, innovation, and collaboration drive both commercial growth and social impact. You’ll be empowered to make data-driven decisions and clear cases for prioritization of solutions in a domain that you have a high degree of ownership over.

You’ll be joining a team that’s rapidly expanding our credit and underwriting capabilities. We are looking for someone who loves building predictive models, analyzing complex data, and solving challenging, ambiguous data problems — if that sounds like you, you might be a fit!

In this role, you would be responsible for:

• Building and refining credit scoring models to assess customer creditworthiness and default risk
• Analyzing M-KOPA’s repayments data and other data sources to continuously improve our loan eligibility criteria while managing credit risk
• Developing machine learning models for loan eligibility decisions and pricing optimization
• Refining loan pricing based on credit analysis, predictive modeling, and customer behavior
• Testing new types of loans to understand customer demand and credit performance through A/B testing and statistical analysis
• Monitoring credit performance to detect risk shifts and quantify margin impact using advanced analytics
• Testing the predictiveness of new data sets and feature engineering for enhanced model performance
• Using Python, SQL, and other tools for data analysis and model development
• Collaborating with data scientists to implement and scale machine learning models in production

This role can be remote or hybrid, but candidates must be located within our time zones (UTC -1 to UTC+3) to ensure effective collaboration with teams across our multiple locations.

Your application should demonstrate:

• Several years of experience building predictive models, particularly credit scoring, risk models, or similar classification/regression problems
• Strong machine learning background with experience in model development, validation, and deployment
• Advanced statistical modeling and quantitative analysis skills, including experience with model evaluation metrics and performance monitoring
• Proficiency in Python, SQL, and relevant ML libraries (scikit-learn, pandas, numpy, etc.)
• Experience with 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
• Strong interpersonal and collaboration skills
• (Highly desirable) Experience in credit, underwriting, lending analytics, or fintech modelingCredit accessibility and affordability are at the core of this role. You’ll join a small, high‑performing team where every day brings new modeling 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.