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Hello! I'm Kathlyn "Kat" Le

BUSINESS STRATEGY | ANALYTICS | PRODUCT

COMPANIES I'VE WORKED FOR

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Education

B.A. Business Administration
Emphasis in Operations & Decision Technology
Minor in Digital Information Systems
Diploma Earned December 2022

M.S. Business Analytics
Graduate Certificates: AI in Business &
Product Management
Expected Graduation: Dec 2026

Get to Know Me!

Want to hear a little bit more about my experience, background, hobbies, and more?

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USC Graduate Women in Business

USC Trojan Sports Research Lab

USC Interactive Gaming Association

USC Marshall Product Club

UC Irvine Sports Business Association

alpha Kappa Delta Phi Sorority

Certifications

PORTFOLIO

PROJECTS

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Title

Title

ASUS Go-to-Market ROG R1 Gaming Glasses

Formulated a comprehensive commercialization and market growth strategy for the ASUS ROG XREAL R1 Gaming AR Glasses, targeting the high-growth handheld gaming segment (ROG Ally ecosystem) and mobile power users. Operating without internal historical data, the project established a first-principles estimation model to evaluate market potential, pricing dynamics, and cross-hardware ecosystem synergies.

WMG Music + Content Strategy

WMG Music + Content Strategy

WMG Music + Content Strategy

This project was a collaborative effort within a cross-functional intern cohort at Warner Music Group (2022), where I worked as the Viral Marketing & Analytics Intern.

I partnered with other interns specializing in Pop/Rock Marketing, Publicity, Video Production, and Sales & Streaming to develop a comprehensive Music and Content Strategy.

StudySpot AI App

StudySpot AI App

StudySpot AI App

Developed for the USC AI Global Case Competition, StudySpot is an AI-integrated mobile prototype designed to eliminate the "productivity tax" of searching for study spaces. Serving as both Product Manager and Engineer, I led the end-to-end development of our MVP, from defining the product roadmap and user personas to architecting the technical integration of natural language search. The prototype leverages AI to translate subjective user needs (like "quiet vibes" or "group-friendly") into data-driven location recommendations, providing a seamless solution for students in high-pressure environments.

ATP Sports Strategic Analysis

ATP Sports Strategic Analysis

ATP Sports Strategic Analysis

This project leverages historical ATP match data (2016–2025) to uncover the hidden variables that drive deep tournament runs in men's professional tennis. The analysis is divided into two primary machine learning pipelines: a supervised learning approach to predict which players will advance to the semi-finals of a Grand Slam, and an unsupervised approach (PCA and Factor Analysis) to define the underlying skill profiles required for different court surfaces (Hard, Clay, Grass).

To account for extreme target variable imbalance—as only 3-4% of a 128-player draw reach the semi-finals—we utilized SMOTE and evaluated models based on F1-Score rather than raw accuracy. The Random Forest model proved highly capable of capturing complex style interactions, successfully predicting semi-finalists entirely blind to player rankings or past performances.

The Well Edit (Digital Innovation Project)

The Well Edit (Digital Innovation Project)

The Well Edit (Digital Innovation Project)

Project Overview
The Well Edit is a high-fidelity MVP and business strategy for a multi-sided social commerce platform. Recognizing a gap in the $665B wellness market, I conceptualized a zero-inventory marketplace that leverages AI and graph databases to match users with their biological "Skin Twins."

The Solution:

AI-Driven Trust: Utilizes edge-processed biometric scanning to build a peer-validated discovery loop, completely bypassing traditional influencer marketing.

Frictionless Commerce: Integrates retail APIs (Sephora/Ulta) directly into the interface for a seamless "Shop the Shelfie" experience.

Scalable Architecture: Designed a high-trust, community-led platform capable of generating high-converting affiliate revenue without the overhead of physical inventory.

Kickstarter Campaign Analysis

Kickstarter Campaign Analysis

Kickstarter Campaign Analysis

What separates a fully funded Kickstarter campaign from one that falls flat? In this project, I performed an end-to-end exploratory data analysis and time series forecast on Kickstarter platform data to uncover the key drivers of crowdfunding success.

Key Contributions:

Cleaned and transformed complex raw dataset for reliable statistical analysis.

Designed advanced visualizations—including dual-axis trend lines, pyramid charts, and diverging bar charts—to compare campaign performance across major categories.

Engineered time series models (Optimized Moving Average and Autoregression) to analyze historical launch and funding trends over time.

Delivered a fully reproducible, clean HTML/PDF data report generated directly from Google Colab.

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CONTACT

CONTACT ME

Feel free to reach out to discuss opportunities, projects, or collaborations. I'm excited to connect and explore new ventures!
lekathlyn05@gmail.com

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