E-commerce Product Classification and Insights:Managed metadata updates and ensured data integrity for 300+ companies via platform tools.Automated data extraction processes using API integrations for efficient data handling.Developed and implemented a scalable keyword classification system for 300+ companies, achieving 99% accuracy.Digital Economy Index and Reporting:Led the generation of market insights and reports, including analysis of market parameters and trend forecasting for 300+ companies.Produced detailed reports for critical events and market trends to support decision-making.Ad-hoc Data Engineering Projects:Implemented automation solutions for custom metrics and dimension mapping, reducing mapping time from 15 minutes per metric per company to under 50 minutes for 300+ companies, a 95% reduction in time.Designed and enhanced ETL processes to ensure high-quality data for analytics and reporting, improving data processing efficiency by 40%.BERT Model Implementation for Product Classification:Applied machine learning techniques, including BERT models, to improve accuracy in product categorization from 90-92% to over 99%.Reduced manual classification efforts equivalent to 2 weeks of work per resource to zero by implementing advanced AI models.Utilized Python and PySpark for deploying advanced AI models, demonstrating expertise in data-driven solutions.Migration from Remote Desktop to Databricks:Migrated the entire classification process from remote desktop to Azure Databricks, reducing classification run time from 1 day to 40 minutes (93% reduction) and metadata pull duration from 2 days to 1.5 hours (94% reduction).Successfully transitioned the code base from Python to PySpark, enhancing performance and scalability.