Hi, I'm Josh!

Current status:
Studying computer science and business
at the University of Pennsylvania

I am a junior at Penn pursuing a dual degree between Penn Engineering and The Wharton School. Previously, I've worked as a software engineer intern at Principal Financial Group, data science intern at the CDC, undergraduate researcher at Penn Medicine, web developer for the Korean Language Department at Penn, and teaching assistant at Penn Engineering (ENM 3750) and
Wharton (STAT 4300). I recently signed my offer to join Meta as a Data Science intern for Summer 2025!

My Experience

Here's what I've done professionaly so far!

Data Science Intern @ Meta

Incoming Summer 2025!

Software Engineer Intern @ Principal Financial Group

I worked on a client dashboard for individuals to enroll in a robo-investment service based on their risk aversion. On the frontend, I worked with Next.js in TypeScript React to improve web accessibility. For the backend, I implemented API calls in Java that interact with a NoSQL database — all within Spring Boot microservices.

During the company's intern hackathon, I assumed the role of technical lead for my team. We built a React web app that automates business task assignments, using AWS (Lambda, API Gateway, S3) and Llama 3 endpoints.

Data Science Intern @ CDC

I created programs in R that analyze which characteristics of labs or chemical analytes affect lab performance in the mandatory inspection tests conducted by the CDC. Here, I was able to learn and hone my skills in data engineering, statistical analysis, and data visualization.

Web Developer @ Penn

I designed web-books in HTML/CSS for the Korean Language Department's text book series
("You Speak Korean!").

Teaching Assistant @ Penn

I hold weekly recitations to review material with students, grade assignments, and conduct office hours to provide help with Python/R homework for statistics (STAT 4300) and biological data science (ENM 3750) classes.

Undergraduate Researcher @ Penn Medicine

I learned about machine learning using Python libraries like Tensorflow, and Seaborn. With this knowledge, I tested existing machine learning models and consolidated electronic/physical patient data entries.

Portfolio

Projects made with passion - click project names for Github repository!

Retail Car Price Prediction Program

  • This application analyzes 55,000+ data entries of car sale history and predicts car prices based on make year, model, odometer readings, etc.
  • Machine learning models such as Linear Regression, Random Forest, and Gradient Boosting were used. Feature engineering and fine-tuning was performed as well using one-hot encoded PCA and GridSearchCV.

Robot Compatibility Matching App

  • This Android App programmed in Java was used in the FIRST Robotics Competition to collect real-time data input that is used to assess compatibility of a team's robot with another team. SQLite was also incorporated to organize the inputs and produce conclusions from data analysis.

Bioinformatics Toolkit

  • This program illustrates the DNA transcription/translation process through a graphic user interface coded in Python (Tkinter).
Joshua Lee