I'm a data scientist with a passion for solving complex problems through data-driven approaches. Currently, I work as a Data Scientist III at Walmart, Inc., where I've developed and deployed machine learning pipelines that streamline algorithm retraining and optimize performance. My work focuses on efficient code conversion and cost-effective deployment on the Walmart Cloud Native Platform using Kubernetes.

Previously, as a Data Analyst at Goodie Bag Food Co., I acquired and analyzed data from various sources, designed data pipelines, and built an internal dashboard to track customer behavior and business metrics. During my internship at Walmart, Inc., I developed a data engineering pipeline using Spark and implemented Deep Learning algorithms to predict item sales, significantly reducing the forecasting engine's runtime and model count.

I finished my M.S. in Data Science at the University of Colorado Boulder, where I also served as a Research Assistant. My research includes developing active learning algorithms, implementing topic modeling techniques, and building image mining algorithms to understand consumer preferences.

My academic background in Computer Science and Engineering, combined with strong skills in Python, R, SQL, and various frameworks, equips me to tackle diverse challenges in data science. I've also published research papers on topics like COVID-19 spread prediction and innovative wheelchair control systems.

Driven by a commitment to continuous learning and innovation, I'm eager to apply my expertise to create impactful, real-world solutions in the field of data science.