Senior Data Scientist
CurrentCreated baseline XGBoost models for Payment Risk and Pre-payment Risk and refined both models with additional feature engineering, feature selection techniques like backward stepwise feature elimination, PDP plots, PSI thresholds, IV, VIF etc. Created baseline linear, lightGBM models as well to test performance against XGBoost.Developed an end-to-end framework to rapidly iterate and create these models for other clients. This reduced time taken to replicate similar models for other clients by 60%Created a framework to evaluate different steps of MLOps lifecycle - Development, Deployment, Scoring and Governance. Benchmarked performance metrics at each stage for all the Azure services used in the flow.Developed model governance framework with metrics, monitoring framework and stability thresholds by analyzing at model performance over several vintages/OOT datasets, stress testing inference etc.Streamlined and automated governance metrics generation and reporting processes through python scripts. Deployed scripts on event-driven Azure Functions to automate metric generation as per defined cadence.