Software Engineering, Data Analysis

Fengfeng Sun

***** ******** ****** *** ***, Bethesda, MD 20814

951-***-**** *********@*****.***

EDUCATION

2023.07-2024.10, Arizona State University Tempe, AZ, USA Master’s degree in computer science. GPA: 4.0

2021.09-2021.12, University of California Riverside Riverside, CA, USA Undergraduate course - CS 141 Intermediate Data Structures and Algorithms, grade 2011.09-2013.06, Soochow University Suzhou, China

Master’s degree in Textile Engineering. GPA:3.6

2007.09-2011.06, Soochow University Suzhou, China

Bachelor’s degree in Apparel Design and Engineering. GPA:3.49 CERTIFICATIONS

• Google Advanced Data Analytics, May 2025

• Big Data Professional Certification, Arizona State University, Mar 2024

• Software Engineering Professional, Arizona State University, May 2022 SKILLS

Programming & Analysis: SQL, Python, Java, C++, JavaScript, Scala Libraries & Tools: NumPy, Pandas, Scikit-learn, Matplotlib, Seaborn, TensorFlow, PyTorch, Apache Spark

Data Visualization: Tableau, Power BI

Web Development: HTML, CSS

PROJECTS & TRAINING EXPERIENCE

Taxi Cab fares prediction

Tools: Python(Numpy, Pandas, Scikit-learn, Matplotlib, Seaborn),Tableau

• Performed exploratory data analysis (EDA) on 20,000+ taxi fare records to uncover trends, anomalies, and fare-related patterns.

• Built and evaluated a linear regression model to predict taxi fares. Classifying a TikTok video as a claim or opinion

Tools: Python(Numpy, Pandas, Scikit-learn, Matplotlib, Seaborn),Tableau, XGBoost

• Conducted exploratory data analysis (EDA ) on 20,000 TikTok video listings to uncover key patterns and insights.

• Built and evaluated Random Forest and XGBoost models to predict if the TikTok video is a claim or opinion, comparing performance to identify the more accurate predictor. Creating Database Using Microsoft SQL Server

Tools: Microsoft SQL Server

• Designed and implemented a relational database in Microsoft SQL Server to store and manage data from six CSV files.

• Performed data cleaning and standardization to ensure consistency and integrity across related tables.

• Created SQL views to join and present related tables, enabling streamlined access for future data analysis and reporting.

Hot Spot Analysis on NYC Taxi Trip Data

Tools: Apache Spark, Scala, Spark SQL

• Configured the Apache Spark environment and developed Scala code using Spark SQL to interact with a relational database.

• Executed complex queries to extract spatial and temporal data from the NYC Taxi Trip dataset.

• Calculated the "hotness" of geographic rectangles by computing the Getis-Ord Gi* statistic.

• Identified the top 50 spatial hot spots based on descending G-scores to detect areas of high taxi activity.

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