Hello, my name is Daniel. I'm a data enthusiast with a passion for uncovering insights through analytics and machine learning. My projects have ranged from tackling Kaggle challenges—like my Ames, Iowa housing analysis—to building interactive R-Shiny applications that explore democratic backsliding. I've also delved into data scraping to examine university retention rates and, for my capstone, analyzed how grocery store proximity and density influence housing values. I enjoy tweaking code to make sure everything flows as smooth as butter, and is understandable to both a technical and non-technical audience. With a strong foundation in Python, R, and data visualization, I'm seeking opportunities in data science, analytics, or any role where I can turn raw data into meaningful decisions.
