Data science student focused on operations strategy, data analytics, and AI prediction models. I build practical machine learning and automation workflows that turn messy data into clearer decisions.
A dedicated Data Science major at the University of Wisconsin-Madison with a technical foundation in statistical analysis, machine learning algorithms, and software development, plus more than five years of work experience in fast-paced team environments.
I combine coursework in probability, computer science, and machine learning with hands-on operational leadership. My strongest lane is using data analysis, AI tools, and automation to improve workflows and make teams more effective.
Bachelor of Science in Data Science at the University of Wisconsin-Madison. Expected graduation: May 2028.
Associate Consultant at Krahnborn, contributing to data-driven solutions, automation strategies, and more accurate client deliverables.
Python, NumPy, Pandas, PyTorch, R, Java, statistical analysis, linear algebra, regression models, clustering algorithms, and machine learning models.
Operational workflows, team leadership, mentoring, customer service, professional AI leveraging, and cross-functional collaboration.
Contribute to data-driven solutions and automation strategies in a consulting environment. Leverage AI tools, machine learning frameworks, LLM prompting, and data analysis techniques to reduce manual overhead and improve decision-making processes.
Promoted to Bar Manager after demonstrating reliability and leadership excellence. Led staff coordination for high-volume university venues and helped maintain smooth service during peak hours and events.
Delivered interactive digital document products for public and private clients. Closed 20+ projects with a 100% customer satisfaction rate while meeting strict cloud-based quality standards.
A selection of my most relevant work, from an award-winning sales prediction model to a from-scratch transformer and a course-advising AI assistant. Each public project links straight to the source on GitHub.
Collaborated with a team of four to engineer a Python-based machine learning model that analyzed historical sales data and predicted promotional windows where discounts would maximize profitability.
View resume highlightA from-scratch, ~10M-parameter decoder-only transformer built in PyTorch and trained on the Linux source tree. Implements causal (lower-triangular) masked self-attention and auto-detects CPU/CUDA for training.
View repositoryMadData 2025 hackathon project: an AI assistant that helps UW-Madison students pick relevant coursework. Combines Madgrades and Rate My Professor data with FAISS vector search to recommend classes better than the default course selector.
View repositoryMachine learning project that splits user/log data into train and test sets, trains a logistic regression classifier, and tunes it to reach over 75 percent accuracy.
View repositoryFlask weather application for city search with current conditions, humidity, wind speed, and short-term forecasts pulled from the OpenWeatherMap API, wrapped in a clean responsive UI.
View repository