👋 Hello! I am Haiying Lin, a Business Analyst leveraging advanced data analytics to drive data-informed and actionable decisions and boost business performance. My experience spans industries including IT services and financial services, where I have improved business outcomes by utilizing data to uncover insights and drive strategic decisions.

🔧 Technical Skills Data Analytics: Statistics, Data Analysis, Business Analysis, A/B Testing, Data Mining, Root Cause Analysis, Jupyter Notebook, Python, R, Julia, NumPy, pandas, SciPy, Scikit-learn, Excel (VBA, pivot tables, array functions, power pivots, etc. Data Visualization: Data Dashboard, Tableau, Power BI, Excel, Matplotlib, Seaborn Database: SQL, MySQL, SQL Server, PostgreSQL, NoSQL

🎓 Education Master of Science in Business Analytics, University of California, Riverside (09/2023 – 12/2024) Data Analytics for Business Certificate, University of California, Irvine (09/2022 – 06/2023)

🏆 Projects IBM HR Analytics Employee Attrition & Performance (Programming language: Julia and R) -Conducted an in-depth analysis IBM employee records to identify key factors influencing employee attrition and performance to enhance HR strategies by predicting employee turnover and identifying performance drivers. -Utilized Step Forward Selection and Lasso Regression to distill the dataset from 35 potential predictors to 14 significant variables, balancing model accuracy and computational efficiency. -Developed multiple predictive models using Logistic Regression, K-Nearest Neighbors, Linear Discriminant Analysis (LDA), Neural Network Classifiers, and Multinomial Classifiers, implemented k-fold cross-validation to assess model performance -Identified the model with the highest accuracy and best F1 score significantly aiding HR decision-making processes

Bank Telemarketing Project (Programming language:R) -Analyzed over 5k+ records from a banking telemarketing campaign focused on term deposits using R and Python and conducted data cleaning, exploratory data analysis, and data description. -Employed K-means clustering to segment customers and identify the target segments with the highest term deposit subscription rates and then used Lasso regression for variable selection to identify the most critical independent variables. -Applied various predictive modeling techniques, including Logistic Regression, K-Nearest Neighbors, Decision Tree, and Support Vector Machine. -Derived actionable insights and key metrics to evaluate customer potential and provided strategic recommendations to improve term deposit conversion rates by targeting the identified high-potential customer segments.

💼 Professional Experience Data Analyst Intern | Cozii Technologies (03/2024 – 08/2024) Enhanced product subscription rate by 10% through data analysis and collaboration with sales teams. Built data pipelines with Python and SQL, enabling the creation of actionable dashboards.

Data Analyst | Bank of Dongguan (05/2022 – 09/2022) Increased user engagement on the digital banking platform by 13%. Provided insights on market trends to improve decision-making.

Intern | BDO China (01/2022 – 04/2022) Improved audit accuracy by 15% through data validation and process optimization.

🚀 Let's Connect! Feel free to reach out to me on LinkedIn or via email at [email protected] for collaboration or networking!