• Enhanced MySQL stored procedures, significantly improving database performance. This optimization resulted in a 25% reduction in processing times, allowing for faster data retrieval and improved overall system responsiveness.

• Implemented database normalization techniques to eliminate data redundancy and improve data integrity.

• Executed a seamless data migration strategy, minimizing downtime and ensuring business continuity. This involved careful planning and execution of data transfer processes, with minimal disruption to ongoing operations.

• Selected for a competitive data science fellowship with students from across the 11 CUNY senior colleges where Fellows create technical projects using tools such as Python, Pandas, Numpy, Scikit-learn, and SQL.

• Participate in weekly courses and learn industry best practices for exploratory data analysis (EDA), feature engineering, data collection and processing, statistical modeling, data visualization, machine learning techniques, data science process, and big data.