Data Sciencntist

Wendy Hu

202-***-**** ******@**********.*** https://www.linkedin.com/in/liwenhu1999/

EDUCATION

Georgetown University, Washington, DC, USA Expected May 2026 MS in Data Science & Analytics (GPA 3.89/4.0)

Coursework: Data Science and Analytics, Probabilistic Modeling and Statistical Modeling, Database Systems and SQL, Advanced Data Visualization, Statistical Learning, Data Structure, Objects and Algorithms in Python National Taiwan University (NTU), Taipei, Taiwan Jun. 2022 BSW in Social Work (GPA 3.8/4.3)

TECHNICAL SKILLS

• Programming and Tools: Python (Pandas, Numpy, scikit-learn), R, C++, SPSS, SAS, SQL, AWS, GIS, tkinter

• Data Science & Statistical Modeling: Monte Carlo Simulation, Pearson Correlation Coefficient, Bootstrap Sampling, Chi-square Test, Bayes’ Theorem, DBSCAN, PCA, Random Forest, Machine Learning, Data Munging, Data Mining

• Data Visualization & Platforms: Excel, Python (matplotlib), R (ggplot2), Looker studio, Tableau, Data Cleaning, Data Manipulation, Vega-Lite, D3.js

PROFESSIONAL EXPERIENCE

Data Scientist / Founding Member Taipei, Taiwan

Data Hub Aug. 2023 – Present

• Analyzed quantitative surveys on gender-friendly services in government sectors using Pearson Correlation analysis and PCA, uncovering insights that informed policy improvements and enhanced inclusivity in government services.

• Led factor analysis on psychological well-being dataset using R and visualized findings with ggplot2, developed automatic data pipeline to reducing manual effort by 72%, minimizing human error.

• Collaborated with a team of 10 social workers to develop an interactive dashboard using Looker studio, enabling real- time tracking of casework metrics, improving decision-making efficiency.

• Mentored a cross-functional team of 4 data analysts on data visualization and statistical techniques, boosting their ability to translate complex social case data into actionable insights, increasing team productivity by 75%.

• Established partnership with 5+ NGOs and 10+ organization managers to support them with data analysis, providing data insights for future decisions.

Research Assistant Taipei, Taiwan

Taiwan Association of Medical Screening Sep. 2023 – Dec. 2023

• Utilized SAS to analyze lung cancer screening data of 2,000+ patients from Taoyuan, Taiwan, identifying key trends in low-dose computed tomography (LDCT) screening outcomes. Data Analyst Intern Taipei, Taiwan

Taiwan Mobile Co., Ltd. Apr. 2023 – Sep. 2023

• Developed Selenium web scraping tool integrated OpenAI moderation models, detecting and filtering potential malicious messages from a dataset of 5,000+ inputs, increasing content moderation efficiency by 60%.

• Applied Natural Language Processing (NLP) using the ckiptagger API to identify key words, entities, and frequently mentioned names in Chinese fake news, contributing to the company's anti-fraud strategy and presenting actionable insights to team managers.

PROJECTS

Predict Urban Parking Violation Trends using Machine Learning Oct. 2024 – Dec.2024

• Implemented K-Means clustering, PCA and DBSCAN to construct visualization to distinct clusters to discover linear and non-linear patterns.

• Developed and implemented Random Forest Classification Model achieving 64% accuracy in predicting parking violation types, analyzing 1.2M+ records with 34 variables using Python and scikit-learn.

• Created data visualizations using Python & R libraries to illustrate spatial and temporal trends, revealing critical patterns in urban parking behavior.

Analyze Geospatial, Infrastructure and Price on EV Adoption Trend using Statistical Models Oct. 2024 – Dec.2024

• Conducted statistical analysis impact of geographic location, urban vs rural areas, and charging station density on consumer decision-making for 20,000+ EVs data in Washington State using GIS models.

• Analyzed correlations using statistical modeling between the availability of charging stations and EV range using statistical modeling.

Fund Web Scraping and Visualization: Exploratory Interface Feb. 2023 – Jun. 2023

• Conducted web scraping of 20,000+ fund data from the "Juhong Web" investment website using Python Selenium package for analysis of the best fund investing combination for users.

• Built out front end user interface using tkinter and visualize results using matplotlib.

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