# Shulin Chen

> SWE @ IXL Learning｜  SDE Intern @ NVIDIA   ｜ MSCS @ Columbia University

Location: United States, United States
Profile: https://flows.cv/shulinchen

Committed Computer Science Major with a minor in Statistics from the esteemed University of California, Irvine. My academic journey has provided a strong foundation in coding, algorithms, and statistical analysis, enabling me to adeptly navigate data-driven realms. 

During my transformative internship, I translated intricate theoretical concepts into practical applications. Demonstrating proficiency, I meticulously processed, cleansed, and analyzed extensive datasets. Using tools like Python, SQL, Alteryx, Tableau, Power BI, and advanced statistical methodologies, I extracted valuable insights. I conveyed these insights through engaging visualizations and comprehensive reports, effectively communicating intricate findings to both technical experts and non-technical stakeholders. 

My collaborative efforts within cross-functional teams consistently contributed to resolving real-world challenges and steering data-informed decision-making. Armed with a robust analytical mindset and an enduring passion for maximizing data's potential, my insights consistently improved process efficiencies and pivotal choices. 

Currently pursuing a Master's degree in Computer Science at Columbia University, I will further enrich my expertise. With a blend of creativity and precision, I am poised to embrace new challenges and bridge the gap between academic knowledge and real-world application. I eagerly anticipate contributing to initiatives that redefine industry standards. 

Feel free to contact me at sc5320@columbia.edu to explore potential collaborations or connect on shared interests.

## Work Experience
### Software Engineer @ IXL Learning
Jan 2025 – Present | San Mateo, California, United States

### Software Engineer @ NVIDIA
Jan 2024 – Jan 2024

### Data Analyst @ T-Mobile
Jan 2021 – Jan 2023 | United States
•	Data Forecasting and Machine Learning: Led market share and customer churn forecasting experiments using Python and R on a 100k+ record dataset, achieved 15% better prediction accuracy and reduced customer churn by 5% with machine learning tools like Scikit-learn
•	Visualization and Report Management: Developed a dynamic dashboard using SQL, which later was adopted as an internal management tool, to enhance communication and data sharing across organizational teams in 10+ regions and integrated Power BI and Tableau to create customized reports with actionable recommendations for diverse teams across regions
•	System Modernization with Alteryx and Automation with Python: Employed Python code for data processing and cleansing using libraries such as Pandas and NumPy, applied predictive analytics using libraries like Scikit-learn, TensorFlow, and PyTorch to construct and deploy predictive models, realized the automatic process of report generation adopted by internal teams across 10+ regions, and led to 30% increase in work efficiency
•	Geospatial Data Analysis: Employed Google Maps API to extract geolocation data, categorized the given data using Scikit-learn in Python, and used machine learning algorithms like classification model to help the team identify the optimal cell tower location


## Education
### Master of Science - MS in Computer Science
Columbia University

### Bachelor of Science - BS in Statistics, Computer Science
UC Irvine


## Contact & Social
- LinkedIn: https://linkedin.com/in/shulinchen0415

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Source: https://flows.cv/shulinchen
JSON Resume: https://flows.cv/shulinchen/resume.json
Last updated: 2026-04-11