As a Clinical Data Scientist in the Department of Analytics, Planning, Strategy & Implementation (APSI) at the Brigham & Women's Hospital (BWH), I apply my skills and knowledge in operations research, data science, and healthcare analytics to optimize patient care and outcomes. I have a Master of Science in Operations Research from Northeastern University, where I learned how to use linear optimization, scheduling, probability, and statistics to solve complex problems in various domains. In my current role, I have successfully simulated and optimized the staffing and waiting times for phlebotomy labs using Python and stochastic queuing models, evaluated the user satisfaction and key features of Epic EHR software using R and statistical tests, and conducted literature review to recommend evidence-based strategies for propensity score matching. I have also developed and implemented machine learning pipelines and models in Python and SQL to classify, structure, and analyze medical notes and data from various sources, such as OCR, Apache Zepplin, and SAS. I have published two papers in Springer and Northeastern University on the topics of underwater vehicle design and opioid use disorder, respectively. I have also received multiple certifications and honors, such as the IEEE National Level Project Competition and the 2022 Pillars of Excellence Awards. I am passionate about using data and analytics to improve healthcare delivery and quality, and I am always eager to learn new tools and techniques to enhance my performance and contribution. I enjoy working with and learning from a diverse and collaborative team of professionals, and I strive to uphold the highest standards of excellence and ethics in my work.