work

- spearheaded in-store key business driver (kbd) analysis for gillette and venus blades & razors (b&r), focusing on availability, share of shelf, share of display, and share of feature in uae, saudi arabia, australia, and south africa

- employed sql to efficiently extract relevant data from diverse databases, and utilized python and pandas for intricate data analysis

- applied machine learning techniques using scikit-learn to evaluate the impact of four central kbds, identifying strategies resulting in a potential 5% increase in market share for female b&r and 7% increase in category sales for male b&r across different markets

- developed and implemented a standardized analytical workflow in knime, enhancing efficiency and consistency for future kbd analyses across various combinations of customers, categories, and countries