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M-KOPA
Senior Data Scientist – Credit
Kampala
• Uganda
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M-KOPAProfession (Finance & FinTech, Entry and Basic-level)
Industry (Information technology, software development, data, Entry and Basic-level)
Agriculture, fishing, forestry,Banking, microfinance, insurance,Computers, software development and services,Data/Research,Education, academic,Energy, utilities, environment,Finance & FinTech,Financial Services,Health care, medical,Human resources, talent development, recruiting,Manufacturing,Non-profit, social work,Restaurant, hospitality, travel,Telecommunications,Transportation, logistics, storage,
Seniority (Information technology, software development, data, Finance & FinTech)
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M-KOPA
Finance & FinTech
Description
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.
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
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
Responsibilities
- 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
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