Job Description
About the Role\nAt 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.\n\n### Key Responsibilities\n- Building and refining credit scoring and risk modelling solutions that assess customer creditworthiness, default risk, and loan pricing across multiple markets.\n- Developing and testing ML models for loan eligibility and pricing optimisation through A/B testing and statistical analysis.\n- Continuously improving eligibility criteria by analysing repayment data, engineering new features, and monitoring credit performance for risk shifts and margin impact.\n- Collaborating cross-functionally with engineers, data scientists, and commercial stakeholders to scale models into production.\n\n### Technical Environment\n- Python, SQL, scikit-learn, pandas, numpy, and relevant ML libraries.\n- Predictive modelling, classification/regression, feature engineering, model selection, hyperparameter tuning, A/B testing.\n- Credit scoring, underwriting, loan pricing, risk analytics.\n\n### Team Approach\n- Low-ego environment where diversity, innovation, and collaboration drive both commercial growth and social impact.\n- High degree of ownership over your domain — you're empowered to make data-driven decisions and prioritise solutions.\n- Cross-functional collaboration with engineering, product, and commercial teams across multiple countries.\n- Analytical rigour combined with deep market understanding to serve customers excluded from formal financial services.\n\n### Qualifications and Experience\n- BA/BSc/HND in a relevant field.\n- Experience building predictive models, particularly credit scoring, risk models, or similar classification/regression problems.\n- Strong machine learning background with hands-on experience in model development, validation, deployment, and performance monitoring.\n- Proficiency in Python, SQL, and relevant ML libraries (scikit-learn, pandas, numpy, etc.) with experience in feature engineering, model selection, and hyperparameter tuning.\n- Experience translating complex model outputs into actionable business strategies and stakeholder communications.\n- Ability to work cross-functionally with product, engineering, and commercial teams.\n- Strong data communication skills — written, oral, and visual.\n- Experience in credit, underwriting, lending analytics, or fintech modelling.\n\n### Benefits\n- Fully remote Data Scientist role within UTC -1 to UTC +3 time zones.\n- Work with diverse teams across UK, Europe, and Africa.\n- Professional development programmes and coaching partnerships.\n- Family-friendly policies and flexible working arrangements.\n- Well-being support and career growth opportunities.\n\n### How to Apply\nInterested and qualified? Go to to apply online.
