MIS · Santa Clara University
Turning data into practical insight.
Background
I'm a Management Information Systems student at Santa Clara University with a focus on data analytics, machine learning, and business-oriented problem solving. I enjoy work that sits at the intersection of technical depth and real-world impact.
Through coursework and hands-on projects, I've built end-to-end machine learning pipelines, designed relational databases, and led a team through a 24-hour AI hackathon. I'm currently exploring early-career opportunities in data analytics and data science.
Outside of data, I care about clear communication — knowing how to explain what a model does and why it matters is just as important as building it.
Work
End-to-end machine learning pipeline to predict customer purchasing behavior and identify revenue drivers. Built with exploratory data analysis, feature engineering, and multi-model comparison.
Models compared: Decision Tree · Random Forest · XGBoost · KNN
Predicts Uber booking outcomes (Completed vs Not Completed) using ML models with EDA, cross-validation, and business insights.
View Project →Relational schema and full implementation for an Amazon-style e-commerce database. Includes 3NF normalization, ERD, SQL queries, joins, and views.
View Project →AI-powered hackathon MVP that alerts drivers to approaching emergency vehicles. Led a 5-person team from concept to pitch using AWS Bedrock and SageMaker.
View Project →Get In Touch
I'm actively exploring internship and early-career opportunities in data analytics and data science.