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Data Scientist – Credit Eligibility
M-KOPAData Scientist at M-KOPA building predictive models for credit eligibility and pricing across African markets. Collaborating with various teams to enhance financial inclusion for underserved customers.
Tech Stack
Tools & technologiesNumpyPandasPythonScikit-LearnSQL
About the role
Key responsibilities & impact- 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
Requirements
What you’ll need- Experience building predictive models, particularly credit scoring, risk models, or similar classification/regression problems
- 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
Benefits
Comp & perks- 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
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
credit scoring modelspredictive modelsrisk modelsmachine learningmodel developmentmodel validationmodel deploymentperformance monitoringfeature engineeringhyperparameter tuning
Soft Skills
collaborationdata communicationstakeholder communicationcross-functional teamworkanalytical skills