Yeying Zhuo

Developed an AI-powered knowledge base for test readouts and media mix modeling, shaping $600M in test planning. Led geo-experimentation and capital reallocation models, informing $284M in budget decisions and redirecting $59M to high-return opportunities.

Engineered large-scale data pipelines for inventory forecasting and shrink across 50M+ SKU-level events, reducing $15M revenue loss. Delivered near real-time inventory dashboards, raising in-stock rate by 15% and reducing shrink by 5%.

Unified 5K+ student records and standardized data validation across 20+ stakeholders, cutting reporting errors by 30%. Monitored student performance via descriptive analytics, raising success rates by 15% for 200+ students.

Conducted sentiment analysis on 1TB of Glassdoor reviews using text-mining to quantify risk and inform policy underwriting. Deployed web scraping models to reconcile LinkedIn/CRM data discrepancies, boosting data quality for 30+ teams.

Identified $2.5M in revenue opportunities by analyzing customer portfolios and recommending high-ROI products. Led weekly business reviews with senior leadership to assess performance and shape next-quarter product promotion strategy.

Grade: 3.94 out of 4.0

Activities and societies: Research Project: Developed an image recognition system for avian species classification using deep learning (CNN) and K-Means clustering; preprocessed and trained on 50K+ bird images using TensorFlow, achieving 92% classification accuracy.

Completed a Master of Science in Data Science with a GPA of 3.94 out of 4.0. Developed an image recognition system for avian species classification using deep learning and K-Means clustering, achieving 92% accuracy.

Activities and societies: Full Merit Scholarship

Earned a Bachelor of Business Administration in Finance and Accounting. Awarded a Full Merit Scholarship.