Senior Data Scientist - Credit

Day to day, you'll be:

• 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

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

​​​​​​​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:

• 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