A Data Science graduate from NUS, currently driving AI innovation at Johnson & Johnson. I specialize in bridging the gap between statistical modeling and real-world supply chain applications. With a background spanning HR analytics, nutritional studies, and global supply chain operations, I bring a data-first approach to solving complex business challenges.
My focus is on leveraging Artificial Intelligence to optimize processes, predict trends, and create actionable insights from massive datasets.
Analyzed nutritional status of children across 4 SE Asian countries. Built a dashboard to visualize data and implemented ML models to predict malnutrition status (stunting) for FrieslandCampina.
Created a robust dashboard tracking key people KPIs (women in leadership, departure reasons) at Schneider Electric. Automated monthly reporting processes to increase efficiency.
Leveraged data analytics within the Technology Leadership Development Program at J&J to drive efficiency in supply chain operations and reduce logistics costs.