CV

Daniel Cheung (this is not a legal name, it’s a preferfed name)

Informal, but the same content with formal version, which is on a letter size paper pdf or printed one.

Phone: (516) DAY - RDNA
Email: danielhcheung@outlook.com
Website: danieldata.com
LinkedIn: linkedin.com/in/daniel-zhang-2021data

Summary

Master’s student in Data Science at Stony Brook University with a strong foundation in statistics and programming. Skilled in Python, R, and SQL with hands-on experience in Flask, FastAPI, and cloud deployment. Proven track record of optimizing code performance, developing machine learning models, and building microservices. Ranked top 3 in undergraduate cohort; award-winning experience in statistical competitions.

Skills

• Programming: Python, R, MATLAB, SQL (MySQL), C++, Java, SAS, SPSS
• Frameworks / Tools: Flask, FastAPI, pandas, Docker, Azure, Linux
• Core Expertise: Data Processing, Statistical Modeling, Machine Learning, Data Visualization, Microservices

Education

Stony Brook University – Stony Brook, NY
Master of Science in Data Science
Aug 2025 – Expected Dec 2026

• Coursework: Probability, Data Analysis, Data Structures & Algorithms; upcoming Machine Learning and Big Data
• Practicing deployment with Azure Student Pack (Linux, Docker, VM services)

Zhejiang Wanli University – Ningbo, China
Bachelor of Science in Statistics — GPA: 4.17/5, Top 3 of 103
Sep 2020 – Jul 2024

• Competed in CUMCM Mathematical Modeling Competitions (MATLAB-based solutions to real-world problems)
• Conducted survey-based projects with regression & clustering methods for service analysis
• Co-founded Computer Repair & Tech Club: deployed Docker services (even on ARM routers with OpenWRT), led workshops on system troubleshooting, and developed an internal Python (Flask)-based printing system

Experience

Python Developer Intern – Hangzhou Mihe Electronic Devices
Mar 2024 – May 2024

• Refactored socket-based microservices into Flask for modularity and maintainability
• Optimized computational pipelines using pandas, cutting runtime by 20%
• Developed web scraping and file-downloading scripts, resolving recurring server downtime issues

Projects

Elderly Care Survey Analysis

• Applied logistic regression and clustering to identify service satisfaction drivers
• Provided actionable insights to improve elderly care programs

Flask-Based Programs

• Designed and deployed a web print solution for campus use, running on microservers and Azure VMs
• Built e-flight log and local financial quote proxy (cached hub), some connected with tg-bot for user interface

Financial Modeling Research

• Experimented with sentiment analysis of investor comments for predictive features
• Graduation thesis on volatility modeling with high-frequency trading data (5-minute intervals) using Lasso regression

Awards

• Third Prize – Provincial Statistical Survey Competition (Nov 2022)
• Third Prize – Provincial Market Survey Competition (Apr 2023)