About

Applied Mathematics student at UC Berkeley specializing in machine learning and statistical modeling. Passionate about leveraging AI and data science to solve complex industry problems and create impactful solutions.

Currently focused on developing ML models and analytics pipelines at Motorola Solutions, while previously using data analytics to optimize supply chain operations at Driscoll's.

Experience

May 2024 - Present

Data Science Intern · Motorola Solutions

Leading development of ML algorithms for large-scale radio configuration analysis, processing 10,000+ radio configurations. Engineered automated data pipelines and conducted cross-functional product design research through statistical modeling and user experience analysis.

Python
SQL
Machine Learning
Data Science

May - Aug 2023

Data Analyst Intern · Driscoll's

Engineered data validation processes and automation systems improving forecast accuracy by 90%. Developed real-time analytics dashboards integrating multi-source data for supply chain optimization.

Python
Excel
Tableau
Data Analysis

View Full Résumé

Projects

BerkeleyNest

Full-stack ML platform analyzing Berkeley's rental market using cloud infrastructure. Engineered automated data pipeline processing 5000+ listings with real-time visualization. Implemented TensorFlow models achieving 92% accuracy in price predictions.

Source Code

Python
SQL
Web Scraping
Google Cloud

TicketSaver

Scalable analytics platform monitoring concert pricing across 5000+ events using cloud infrastructure. Engineered automated ETL pipeline with NoSQL database for real-time price tracking and trend analysis.