Lead Data Scientist | Credit Risk & Alternative Credit Scoring Specialist (Anonymized)

Led the development of alternative credit scoring models leveraging mobile money, behavioral, and transactional data. Improved loan default prediction accuracy by 27% through advanced ensemble machine learning techniques and feature engineering. Built automated production-grade machine learning pipelines utilizing Python, Airflow, and cloud infrastructure. Developed robust fraud detection and early-warning risk mitigation systems for digital lending portfolios.

Built application and behavioral credit scorecards for retail and SME lending portfolios. Conducted rigorous model validation, monitoring, and governance using AUC, KS, PSI, and Gini metrics. Designed interactive analytical dashboards and executive reports for senior leadership using Tableau and Power BI. Optimized underwriting decision systems, resulting in accelerated customer approvals and minimized credit losses.

Analyzed large-scale telecom and mobile money datasets to extract actionable insights and drive customer analytics initiatives. Developed predictive customer churn and segmentation models utilizing machine learning algorithms. Engineered scalable big data workflows utilizing Hadoop and Spark to support enterprise-wide analytics.