Data Scientists Work location- Paya Lebar Use Python and SQL to extract, transform, and analyse large datasets, validate data quality, and investigate anomalies. Enhance fraud detection models for public training grants by developing risk indicators, engineering features, and refining scoring logic. Back-test model changes and recalibrate alert thresholds, balancing precision and recall when investigation outcomes are delayed or incomplete.
Build and deploy a dashboard to monitor model performance, data drift, and concept drift, with alerts for significant changes. Assess new grant schemes and translate eligibility rules, claims processes, and fraud patterns into model requirements. Maintain reproducible code and document model assumptions, validation results, and changes for governance and handover.