Advanced Statistician

Our organization is seeking a seasoned Senior Data Analyst to develop and maintain advanced statistical models that assess customer creditworthiness.

• Design, develop, and validate credit risk models including credit scoring, behavioral scoring, and loss forecasting models.
• Apply advanced statistical techniques (e.g., logistic regression, decision trees, random forests, gradient boosting, Bayesian methods) to predict customer default and credit performance.
• Conduct portfolio segmentation and customer profiling using clustering, Principal Component Analysis, or other dimensionality reduction techniques.
• Collaborate with cross-functional teams to integrate models into decision engines and operational systems.
• Monitor model performance and recalibrate as needed based on changes in customer behavior or macroeconomic conditions.
• Develop risk-adjusted credit policies including approval rules, limit assignment, and pricing models.
• Analyze historical data on payment patterns, usage behavior, and customer demographics to recommend lending strategies.
• Produce model documentation, validation reports, and audit-ready analytics to ensure internal governance.

• Bachelor's Degree or Master's degree in Statistics, Mathematics, Economics, Data Science, Quantitative Finance, or a related quantitative field.
• At least 3 years of experience in Telecom, with expertise in statistical programming tools (Python, R, or SAS) and SQL for data extraction and analysis.