I’m a Data Science graduate student at the University of Houston with a strong foundation in software engineering and a deep interest in machine learning, NLP, and applied analytics. My recent experience includes research in biomedical data modeling and digital phenotyping, and a strategic internship with Inotec – Label Excellence, where I conducted sentiment analysis and market intelligence for RFID and Auto-ID expansion in the U.S. Previously, I worked as a Software Development Engineer at Amazon, contributing to backend service optimization and platform migration using AWS tools like Lambda, SQS, and CloudWatch. I bring a technical toolkit that spans Python, R, SQL, Java, TensorFlow, PyTorch, spaCy, and Spark. I'm passionate about turning data into actionable insights and excited to contribute to real-world solutions at the intersection of data, technology, and impact.