Retail Sales Trial Analysis

Led a comprehensive analysis to evaluate the impact of targeted interventions in trial stores, comparing their performance to matched control stores. Generated insights from 246,742 transactions and customer segmentation data of 72,637 loyalty customers, focusing on lifestyle stage and spending behavior. Designed and executed a control store matching process using similarity metrics, ensuring accurate comparisons and minimizing external influences. Achieved a 7.47% increase in sales in trial stores, primarily driven by premium customers, and delivered actionable recommendations for scaling the strategy. Utilized Python (Pandas, NumPy, Matplotlib, Seaborn) for data analytics and visualization, supporting evidence-based decision- making.

HR Analytics Dashboard

Created visually compelling Power Bi dashboard for the HR department to optimize operations with data-informed decision- making. Successfully calculated and analyzed the company's overall attrition rate, which stood at 16.12%. Discovered a significant correlation between educational backgrounds and attrition, with employees holding degrees in life sciences experiencing the highest attrition rate at 37.55%.

Shipping Data Analysis

Unveiled pivotal insights using python driving operational optimization and informed decision-making in the shipping industry. Led to conclusion that the Port of Tianjin as the highest-value shipping destination, with a total value of $241.7 million, and pinpointed the Port of Shanghai as the lowest-value destination, with $203.4 million in shipping value. Delivered critical insights into global shipping industry, showcasing China as the highest-value shipping nation at $445.1 million. Utilized Python (Pandas, NumPy, Matplotlib, Seaborn) for analysis and visualization.