Jaewon Shim
Portfolio

Data Science major @ University of California, Berkeley

I'm Jaewon Shim, an aspiring data scientist fueled by curiosity and a passion for turning data into impactful insights. With experience at companies like DocuSign and MKS Instruments, I combine analytical rigor with creative problem-solving to bridge the gap between raw data and strategic decision-making. I thrive at the intersection of data, innovation, and storytelling—where numbers drive action and shape meaningful outcomes.

Feel free to connect with or contact me via LinkedIn.

Samsung Stock Price Forecasting

Explore the future of financial markets with this cutting-edge project on forecasting Samsung's stock prices. Leveraging deep learning architectures built with TensorFlow in Python, the model achieved an impressive R-squared value of 0.95, showcasing its predictive accuracy and potential for real-world financial applications.

California Housing Cost Modeling

Dive into the dynamic world of California real estate with an exploratory data analysis of housing costs. Using advanced predictive modeling techniques in Python and the Scikit-learn library, uncover patterns and predict housing prices in one of the most competitive markets in the U.S.

COVID-19 Data Analysis

Gain valuable insights into the global pandemic with a comprehensive exploration of COVID-19 data. Harness the power of advanced SQL queries to reveal trends, uncover anomalies, and make data-driven observations about one of the most impactful events of our time.

Data Science Job Market Analysis

Navigate the evolving job market for data professionals with a deep dive into the world of Data Scientists. This project explores trends, skills, and opportunities in the data-related job market, presenting an engaging overview for aspiring and experienced data scientists alike.

Housing Data in Nashville

Dive into the intricacies of data preparation with this project, focused on cleaning Nashville's housing data using advanced SQL queries. This project demonstrates efficient data wrangling techniques, ensuring clean and actionable datasets for insightful analysis and decision-making.

Scraping Amazon Website

Developed a web scraping tool to extract product names and average customer ratings from the Amazon website. This project showcases the ability to monitor and analyze rating trends over time, providing valuable insights into customer sentiment and product performance.