As a Machine Learning Engineer, I work with various data sources and formats to build scalable and reliable data pipelines using Spark, Python, and SQL. I have automated ETL processes across billions of rows of data, reducing manual work load and improving data quality. I have also designed data pipeline architecture for a microservices project to stream real-time data on a portal, enabling faster and more accurate business insights. I have built and deployed Machine Learning models using MLFlow and maintain them. I have a Master of Science in Financial Mathematics from Stevens Institute of Technology, where I learned how to apply analytical techniques and machine learning tools to solve complex problems in finance and risk management. I have implemented XGBoost models to predict claim severity and optimize business decisions for property and casualty insurance companies. I have also used NLP and text mining to extract valuable information from unstructured data sources. I am currently pursuing an Executive MBA in Business/Managerial Economics from New England College, to enhance my knowledge and skills in business strategy and economics.