Required Experience:

• 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
  

Highly Desirable:

• Experience in credit, underwriting, lending analytics, or fintech modelling
  

• 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