• Applied agile methodologies to improve team collaboration and optimize data analysis workflows, enhancing overall by 30%.• Optimized SQL code for analyzing millions of records, reducing the computation time of key company metrics by 60%.• Analyzed NumPy arrays for numerical operations and Pandas Data Frames for data cleaning, filtering, and transformation.• Led SQL analysis on shopper data to design an A/B experiment and utilized Tableau for pre and post-analysis, demonstrating a 65% email marketing impact.• Executed ad hoc statistical, data mining, and machine learning analyses, developing advanced predictive models with Python.• Implemented MySQL to enhance the product management portal, boosting operational efficiency and data accessibility by 35%.• Leveraged AWS Redshift for data warehousing, enabling high-performance queries and analytics, improving business intelligence and reporting capabilities.

• Employed the Waterfall model to adapt to evolving requirements and develop precise project specifications regularly. • Performed in-depth data analysis using SQL and Excel, extracting actionable insights that enhanced decision-making processes by 40%. • Created interactive Power BI dashboards and reports, improving data-driven decisions across 7 departments. • Developed visually compelling data visualizations with Matplotlib and Seaborn, achieving a 95% success rate in shared insights. • Presented financial data using advanced visualization tools, achieving a 95% clarity rate for internal and external stakeholders. • Facilitated data-driven decision-making by executing data mining and cleaning tasks, enhancing data reliability by 30%. • Monitored AWS and GCP cloud resource costs, reducing expenses by 20% while maintaining effective data analysis solutions. • Ensured data quality through rigorous data cleansing, validating accuracy, and rectifying anomalies, improving data consistency by 25%.