Sr Data Scientist
Current• Experienced in designing and implementing end-to-end supervised & unsupervised machine learning models using Python.• Built predictive models and data-driven analyses to support strategic business decisions.• Built CI/CD Pipelines using Azure DevOps Pipelines (YAML) and Databricks Clusters & Jobs & Notebooks. (REST API, Databricks CLI)• Improved performance by identifying potential claims using supervised machine learning techniques of Gradient Boosting (CatBoost, XGBoost) and Decision Tree / RF. • Created Python package to automate model training process, including compare/monitor model performance with different classification & regression algorithms, hyper-parameter optimization, log performance metrics and artifacts using MLflow and Azure ML. • Provide testing, deployment, maintenance, and performance assessment of existing predictive models.• Certified as MS Azure Data Scientist with running data experiments, train, optimize, deploy machine learning models on Azure Machine Learning and Azure Databricks.• Build customer-facing reporting tools to provide insights and metrics which track ML model prediction performances by using Power BI. • Developed complex SQL queries using joins, sub queries and correlated sub queries to retrieve data from MS SQL database.