Machine Learning Data Science

Zhiyi Zhang

******@********.*** 551-***-**** www.linkedin.com/in/zhiyizhang411

EDUCATION

Columbia University in the city of New York New York, NY MS in Data Science Expected Dec 2025

Courses: Exploratory Data Analysis & Visualization, Applied Machine Learning, Applied Deep Learning Beijing Normal University Beijing, CN

BS in Computer Science and Technology Sep 2018 - Jun 2022

Awards: National Scholarship (1%, 2021), 1st-Class Scholarship (8%, 2020), 2nd-Class Scholarship (15%, 2019)

Courses: Data Structures, Operating Systems, Compiling Principles, Principles of DBMS, Computer Networks PROFESSIONAL EXPERIENCE

MyCOS Data Co., Ltd Beijing, CN

Data Scientist Intern Dec 2023 - Apr 2024

Cleaned and processed 200+ student survey responses using Z-score outlier detection, KNN imputation for missing data, and Min-Max scaling for feature standardization, leading to a 20% improvement in data accuracy for downstream analysis.

Built Python functions for computing educational indicators with pandas, numpy, and SQL. Automated analysis pipelines, generating insights and data-driven university recommendations with visualizations in Matplotlib and Seaborn.

Beijing DeepGlint Technology Co., Ltd Beijing, CN

Product Manager Intern Sep 2023 - Dec 2023

Conducted surveys, analyzing responses with Python (pandas, seaborn) and SQL to identify emerging trends and customer insights.

Designed Axure prototypes, translating customer needs into wireframes and user flows. Led cross-functional meetings to align engineering, design, and business objectives. Kuaishou Technology Beijing, CN

Algorithm Intern Oct 2021 - Dec 2021

Initiated the SPU Tags-Based system, creating user interest tags and integrating product links through a unified data pipeline, enhancing commodity recall effectiveness.

Implemented the Skip-Gram model in the broadcaster recommendation system, increasing product consumption by 6% and boosting user engagement.

PROJECTS

LEAP Climate Data Science Hackathon, First Prize New York, NY Group member Jan 2025

Improved a newly released benchmarking dataset, ChaosBench, by integrating machine learning models for sub- seasonal to sub-seasonal climate modeling and prediction. Predicting Blue-Chip Company Financial Trajectories New York, NY Applied Machine Learning course project Nov 2024 - Dec 2024

Cleaned and transformed Fortune 1000 and SEC 10-K data, handling missing values, encoding categorical features, removing multicollinearity, scaling numerical features, and addressing class imbalance with SMOTE and resampling.

Built regression and classification models to forecast market cap and classify profitability. Used linear and ridge regression, neural networks with L2 regularization/dropout (R = 0.73), and optimized classification with class weighting, resampling, and SMOTE (AUC = 0.93).

American Interdisciplinary Contest in Modeling, Honorable Mention Beijing, CN Leader of a three-person team Jan 2021 - Feb 2021

Led group study meetings to coordinate research, strategy, and writing, ensuring a unified team approach and successful completion of the competition paper.

Developed a PageRank-based musician network to quantify influence, performed feature engineering for similarity analysis, and visualized insights using Matplotlib, driving key findings for the competition. TECHNICAL SKILLS

Data Science & Machine Learning: Python (Pandas, NumPy, Scikit-learn, PyTorch), R (ggplot2, dplyr), SQL Software Development & Engineering: C++/C, Java, HTML, Hadoop, Spark, Git Business & Product Analytics: Axure, Tableau, Power BI, Microsoft Office (Excel, PowerPoint, Word)

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