I was a data science intern at Procter & Gamble, where I analyze usage and customer behavioral data to recommend changes in the content and system for improving KPIs. I also implement regression models and decision tree algorithms to predict faulty consumer packaged goods with up to 80% accuracy, using Python, R, and SQL. Additionally, I create real-time dashboards to monitor the smooth functioning of 10+ manufacturing plants, using Power BI and R. I am pursuing a Master's in Business Analytics at the University of Cincinnati Carl H. Lindner College of Business, where I received a Customer Discovery Research fellowship as part of the Lab2Market program. This program allows me to better understand the market applications of research and develop entrepreneurial skills. Previously, I worked as a CX Senior Analyst at Dentsu, where I leveraged text and sentiment analysis to identify profitable Promoters vs. Detractors for one of the biggest social media companies. I also developed predictive models using supervised and unsupervised machine learning algorithms on AWS to uncover industry and customer insights. My goal is to apply my data science and analytics skills to real-world challenges and become an analytics leader who can drive positive change in the industry. I am passionate about learning new technologies and contributing to open-source projects. I also enjoy reading books and exploring new domains.