Liyan Jin Email & Phone Number

• Customer Detector
• To assist fundraising managers in reducing operational costs and optimizing the donor acquisition process, built an end-to-end Donor Detection system using binary classification models.
• Acquired an online dataset of 6.8 million donors; performed exploratory data analysis (EDA), data cleaning, preprocessing, feature engineering, and feature selection; addressed the challenge of big data analysis by.
• Achieved a ROC-AUC of.93, increased precision from.56 to.90, potentially adding $25 million in annual donations. Wrapped the best-performing Random Forest model as a Flask App and deployed it on GCP.Sales Forecasting
• To support political fundraising managers in effective financial planning and resource allocation, developed a Donation Forecasting model to predict monthly donations using a 10 GB time series dataset.
• Collected and organized data, implemented label and frequency encoding, conducted EDA, and generated new features from timestamps. Built and fine-tuned Linear Regression and ARIMA models.

Phoenix, Arizona, United States

• Received the Outstanding Chair Award in 2020 and 2022.Optimizing Leadership Development with Machine Learning
• To enhance leadership training and employee satisfaction, defined six Servant Leadership components as features and Employee Satisfaction as the target.
• Collected data using online surveys from an E-commerce organization, addressed missing values and outliers, and applied diverse machine learning models (Linear Regression, Polynomial Regression, Lasso, Ridge, Random.
• Considering the computational cost, interpretability, and metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), and R-squared (R²), the Random Forest model emerged as the top performer. Enhanced.
• To reduce technostress and improve well-being among employees at U.S. higher education institutions, segmented employees based on levels of Technostress, including techno-overload, invasion, complexity, insecurity, and.
• Utilized data collection and preprocessing techniques, applied Principal Component Analysis (PCA) for dimensionality reduction, trained, evaluated, and tuned machine learning clustering algorithms (K-means.

• Analysis of Individual Donation Intention
• To forecast individual donation tendencies toward collegiate' eco-friendly football stadium projects, designed a survey, and collected data through a mix of paper-based and online methods.
• Cleaned data and performed EDA, conducted statistical analyses in SPSS, including Hierarchical Regression, Pearson Correlation, ANOVA, and Student's t-test.
• Improved the predictive power by 64% compared to the baseline model. Offered stakeholders data-driven insights into opportunities and challenges for increasing donations. Presented the research findings at multiple.

Florida Bicycle Safety ProgramRole: Searching reports and journal articles for literature review, conducting data collection and data analysis, and writing reports.

Doctor'S Degree, Health And Human Performance With A Focus On Sport Management

• Received Alumni Graduate Fellowship Award in 2010-2014 • Received the CA Boyd Scholarship Award in 2011 • Received Outstanding.

Post-Doctoral Fellow

Master'S Degree, Sport Management

Bachelor'S Degree, Tourism Management