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

Accomplished Lead Data Scientist with over 9 years of experience engineering production-ready machine learning solutions, alternative credit scorecards, and fintech risk analytics architectures. Backed by a strong academic foundation including a Master of Science in Data Science from the University of Nairobi and a BSc in Statistics & Computer Science from Kenyatta University, they specialize in driving financial inclusion through data-driven credit risk models. Throughout their career across pioneering fintech and enterprise banking ecosystems, they have established a track record of building predictive underwriting tools from the ground up. Their expertise spans developing ensemble machine learning models that leverage mobile money, behavioral, and transactional data to dramatically lower risk, including a proven achievement of boosting default prediction accuracy by 27% for digital lending portfolios. They are highly proficient in designing automated data engineering pipelines and MLOps workflows using Python, Apache Spark, Airflow, and BigQuery. As an AWS Certified Machine Learning Specialist, they possess deep expertise in deploying cloud-native predictive applications and establishing strict model governance frameworks using core validation metrics (AUC, KS, PSI, Gini). Combining technical execution with strategic leadership, they excel at translating massive telecom and transactional datasets into business-critical insights, collaborating with risk and compliance stakeholders, and managing cross-functional technical teams to protect and optimize high-volume asset portfolios.