 Worked contracts with Vertical Bridge & Heritage Plastics Increased profitability by developing precise regression models using Python for optimal product pricing. Enhanced data accuracy through meticulous data cleaning and integration from multiple sources. Improved model reliability by implementing advanced Python libraries (pandas, scikit-learn) for data processing. Optimized inventory levels and production schedules by accurately forecasting demand and sales trends using Power BI. Developed interactive Power BI dashboards, providing actionable insights that increased sales and production efficiency. Strengthened business intelligence capabilities by designing robust SQL data models, supporting analytics initiatives. Increased customer satisfaction using NLP techniques to effectively classify and categorize customer feedback. Corrected performance tuning with Performance Analyzer, slimmer data models, DAX measures, incremental refreshes and star schema designs  Accomplished data processing efficiency through the development of Python ETL frameworks. Mentored junior analysts, reducing project timelines through effective knowledge sharing. Reduced manual effort and enhanced data quality by automating key data tasks utilizing SQL & Python. Ensured accurate and fair employee rewards by developing scalable algorithms for bonus calculations with DAX & SQL. Facilitated management decisions with Power BI dashboards visualizing project expansions Minimized errors and manual effort by automating Excel financial reports using Python. Achieved timely and accurate financial insights with Power BI and Snowflake integrations. Integrated diverse data sources to provide comprehensive performance views.

 Created data accuracy and usability with optimized QA procedures for tabular and cloud models. Raised model performance through comprehensive test plans and data integrity validation. Reduced manual effort by 40% with automated QA processes, streamlining testing workflows using Python. Fueled customer retention by 20% using regression analysis and clustering techniques. Developed performance dashboards in Power BI, enabling informed leadership decisions. Integrated data from multiple sources with SQL to provide a holistic view of business performance.