My data science journey began during a six-month internship at Nestlé in Solon, Ohio, where I focused on inventory management and trailer yard optimization for a global food and beverage network. Collaborating with cross-functional teams, I analyzed data to streamline operations, improve resource allocation, and reduce bottlenecks in high-volume distribution centers. This experience introduced me to the power of data in solving logistical challenges and sparked my interest in leveraging analytics to optimize supply chain performance.I continued to build on this foundation during my internship at Georgia-Pacific in Atlanta, working with the gypsum division. Here, I tackled projects involving shipment forecasting and warehouse automation for building materials. I developed forecasting models to improve delivery accuracy and worked on automation initiatives that enhanced warehouse efficiency. These projects exposed me to the integration of advanced tools into supply chain processes and deepened my understanding of the role probability and statistics play in addressing complex logistical problems.Most recently, at Americold Logistics in Sandy Springs, Georgia, I expanded my focus to transportation optimization and enterprise data capabilities in the cold storage 3PL industry. I worked on optimizing transportation routes, developing a greedy algorithm that minimized empty miles and contributed to a 10% projected reduction in transportation costs. Additionally, I enhanced the company’s enterprise data capabilities by extracting and cleaning billions of rows of order data and creating interactive visualizations to deliver actionable insights to cross-functional teams. These efforts deepened my understanding of how data can transform decision-making in logistics.These internships have shaped my passion for solving complex supply chain problems with data and analytics, ultimately inspiring me to explore machine learning. Supported by the probability and statistics foundation from Georgia Tech’s ISyE curriculum, I’m currently working on a machine learning project to predict retail store demand using historical sales data. Preparing to start my Master’s in Analytics (OMSA) at Tech in the spring, I’m building my technical expertise while actively recruiting for entry-level data scientist roles and internships where I can apply my growing knowledge to create data-driven solutions.