Default Payment Prediction
Description: This project developed a classification model to predict the likelihood of a client having a default payment next month.
Tech Stack: Python; Classification Modeling
My collection of data science projects
A solution-oriented and analytical problem-solver with expertise in data querying and modeling, quantitative analysis, and data visualization. Possessing strong proficiency with SQL, Python, Tableau.
Projects
To see the code/viz, click the image.
HR Analytics Dashboard
Description: This project developed a Tableau dashboard for Human Resource (HR) department, aimed to help HR department gain insights into various aspects of employee data and streamline their decision-making process.
Tech Stack: Tableau; Data Visualization
Risk Case Volumes Forecasting
Description: This project developed a SARIMA time series model to forecast risk case volumes for the year 2023. It aims to help operational managers predict the volume of risk cases based on historical data and the identified patterns and trends.
Tech Stack: Python; Data Visualization; Time Series Modeling
Young Adult Success
Description: This project provides advanced data analysis for UtmostU, a Chicago-based non-profit organization committed to post-secondary success. This project aims to 1) determine the interactions that most positively impact college student success; 2) visualize college journey and path.
Tech Stack: Python; Data Visualization; Classification Modeling
High-value Customers
Description: This project proposed an innovative model that includes RFM analysis, K-means clustering, and decision tree classification to assess the predictive ability of demographic and purchase data in targeting high-value customers.
Tech Stack: Python; K-Means; Decision trees
Bank Customer Churn
Description: This project aims to apply machine learning algorithms to build a prediction model that classifies if a bank customer is going to churn or not.
Tech Stack: Python; Classification Modeling
Cycling Retail Store
Description: This project developed a dashboard using demographic and transaction data from a cycling retail store, aiming to provide stakeholders with marketing and growth strategies by conducting analysis on both customers and products.
Tech Stack: Tableau; Data Visualization
London Bike Sharing
Description: This project aims to utilize historical data of sharing bikes in London and apply time series analysis techniques to predict the weekly demand of sharing bikes in next two years.
Tech Stack: R; Time Series Analysis
Supply, Demand, and Profitability
Description: This project applied the Monte Carlo algorithm to predict Tesla's yearly profit in 2022, 2023, and 2024. Three simulators were proposed: 1) simulating growth rate; 2) simulating correlated growth rate generated by Cholesky decomposition; 3) simulating residuals of time series model.
Tech Stack: Python; Monte Carlo Simulation
Covid-19 Mobility Dashboard
Description: This project developed a dashboard using community mobility data from Google to provide insights into the change of visits in different geographic regions compared to a baseline value.
Tech Stack: Tableau; Data Visualization