Data Scientist Science

Yizhao HONG

E-mail: ************@*****.*** Tel: 646-***-**** SCI profile LinkedIn

EDUCATION

Columbia University in the City of New York New York, NY Master of Arts in Quantitative Methods – Data Science Sep 2024 – Feb 2026

• GPA: 4.0/4.0 (Major Ranking: A+)

University of Science and Technology of China Hefei, CN Master of Management Science in Business Administration – Quantitative Finance Sep 2021 – June 2023

• GPA: 3.9/4.3 (Major Ranking: 1/40)

PROFESSIONAL EXPERIENCES

Data Scientist Intern, Web3Names.ai, New York, NY Oct 2024 – Present

• Developed Python-based web crawlers to extract social graph data from decentralized Web3 platforms, automating the collection of 1,032 data points daily with an accuracy rate of 91.4%.

• Implemented sentiment analysis models leveraging NLP techniques and scikit-learn, combining Logistic Regression and Naive Bayes to classify user sentiments with an accuracy of 87.6%, validated on 10,000+ labeled datasets.

• Leveraged tools like Phantombuster and Owlead to automate messaging workflows, achieving a 34.8% increase in engagement rates and improving the effectiveness of Web3 marketing strategies.

• Designed interactive dashboards using Matplotlib and Tableau to visualize trends in user engagement, product type, and campaign performance, leading to an 17.8% improvement in marketing efficiency and better allocation of AI resources. Data Scientist Intern, Squareone Inc., New York, NY Oct 2024 – Feb 2025

• Collected and analyzed U.S. stocks data in the environmental sustainability sector using Bloomberg Terminal, FactSet, and MSCI ESG Manager, integrating environmental and financial metrics to support ESG-focused investment strategies.

• Developed a multi-factor quantitative model in Python and SQL, leveraging Pandas, Scikit-learn, and Backtrader for backtesting. Combined the model with Monte Carlo simulations to optimize portfolio allocations, achieving a 12.5% reduction in portfolio carbon intensity and 9.3% excess returns over the S&P 500. Associate Manager, Data Science, Zhong De Securities (JV of Deutsche Bank), Shanghai, China Jul 2023 – May 2024

• Utilized time series models (ARIMA) and regression analysis to identify stock and bond trends, improving portfolio returns by 13.6% and supporting 2 refinancing projects, adding 500 million RMB in investments.

• Developed automated financial models in Python to analyze market trends, asset performance, and company financials, reducing manual reporting time by 38.6% and enabling real-time insights for investment decisions. Data Scientist Intern, Kaiyuan Securities, Shanghai, China Jan 2023 – May 2023

• Utilized pivot tables in Excel to analyze operations data of 5,861 clients from 2020 to 2022, including revenue segmentation and geographical distribution, streamlining responses to regulatory inquiries and expediting approval timelines by 15.3%.

• Delivered a 10,000+ word report on company innovations and R&D center project feasibility, utilizing Python to model and optimize budget allocation, land use, and staffing requirements, reducing projected costs by 12.7%. Quantitative Research Intern, Ninth Eternity Securities, Boston, MA Oct 2020 – Dec 2020

• Developed a Black-Litterman Model (BLM) in Python, leveraging libraries such as NumPy, Pandas, and SciPy to optimize asset allocation across stock weights (0.3/0.5/0.7) and rebalancing periods (1/3/6 months). Achieved annualized returns of 10.6%, outperforming the benchmark by 1.7% and the Mean-Variance (MV) portfolio by 1.4%. PUBLICATIONS

• [1] Hong, Y. (2023). Study on the maximum level of disposable plastic product waste. Sustainability, 15(12), 9360.

• [2] Hong, Y., & Cao, C. (2023). Institutional investors’ distraction and executive compensation stickiness based on multiple regression analysis. Journal of Risk and Financial Management, 16(2), 120.

• [3] Hong, Y. (2022). Research on institutional investors and executive compensation stickiness based on fixed effect model — A case study of Chinese listed companies. Mathematical Problems in Engineering, 2022.

• [4] Hong, Y., Hu, M., & Wang, W. (2020). Research on the legitimacy of social enterprises — An interpretation based on the perspective of institutional complexity. Economic Management, 4(5), 341–342, 442. SKILLS & AWARDS

• Computer: Python, MATLAB, SQL, VFP, SAS, Stata, SPSS, Microsoft Office Specialist

• Professional: The Securities Qualification Certificate, ACCA, Certified Data Analyst

• Math: First Prize of the 9th Asia and Pacific Mathematical Contest in Modeling (International Level) Second Prize of the 10th Mathematics Competition of Chinese College Students (National Level)

• Others: Second Prize of the National College Student Big Data Analysis Technology Skills Competition (National Level)

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