Business Analytics Data

FAYE (YUNFEI) WANG

646-***-**** ******@********.*** https://www.linkedin.com/in/yunfei-faye-wang/

EDUCATION

Columbia University New York, NY

MS Business Analytics Dec 2025

GPA: 3.92/4.0.

Courses: Business Analytics (A), Data Analytics (A). Wuhan University Wuhan, China

BS Finance Jun 2024

GPA: 3.83/4.0.

Courses: Financial Engineering (95), Time Series Analysis (93), Investments (96), Fixed Income Securities (94). WORK EXPERIENCE

Deloitte Beijing, China

Quantitative Modelling Intern Jun 2024 - Aug 2024

• Designed a Python-based cross-industry risk transmission model leveraging equity/operational variables, generating 4 key indicators on the nature of 300+ pairwise inter-industry relationships, identifying lead-lag dynamics, and producing forward-looking signals for risk transmission. This model was a key component of the final SaaS product delivered to the client.

• Created a cost-effective web scraping solution using Python/SQL to acquire data, eliminating reliance on paid vendors. Automated the conversion of URL content to PDFs and streamlined data transfers via SSH, contributing to constructing an ETL pipeline for the team.

CCX Green Finance Beijing, China

Climate and Sustainable Finance Intern May 2024 - Jun 2024

• Led a project to develop a CPV (Credit Portfolio View) model to assess climate factors' impact on default rates, managing all aspects from client consultations and requirement analysis to modeling and delivering actionable insights.

• Devised a model quantifying 5 climate factors' impact on a major commercial bank's default rates, achieving 0.958 R (training) and 82% trend prediction accuracy (test) to identify climate risks; final solution was adopted by the client. Founder Securities Shanghai, China

Financial Engineering Intern Jul 2023 - Dec 2023

• Conducted quantitative research on 4000+ A-share stocks to assess how events such as executive stock trades and earnings forecasts affect stock returns: constructed Python algorithms for excess return analysis across various levels, utilizing multi-threading techniques; produced comprehensive visualizations, including interactive 3D graphics; designed an algorithm, involving random trials, to identify stocks sensitive to events.

• Implemented correlation analysis, quantiles, Granger causality, and econometric models (multivariate linear regression and VAR) with Python, evaluated the impact of macroeconomic variables on style rotation of A-share market for over 100,000 data points, and formulated 5 single-indicator strategies, which can generate sustainable excess returns for the long term.

• Executed data-intensive tasks using Python, such as scraping housing data from lianjia.com, accumulating millions of records, enabling research on alternative factors in real estate trends. PROJECTS

Timing Strategy for Bitcoin Trading using Random Forest New York, NY Machine Learning Oct 2024 - Dec 2024

• Engineering a Random Forest model to predict buy/sell/static signals using 5-year hourly BTC price data and technical indicators

(RSI, momentum, volume).

• Achieved a weighted F1-score of 0.67, with a precision of 0.72 for buy/sell signals and recall of 0.87 for hold signals. The test set Outperformed the benchmark with a Sharpe Ratio of 2.53 (vs. 0.50) and a maximum drawdown of - 9.40% (vs. -28.65%). Research on Carbon Emission Allowance Price Wuhan, China Time Series Analysis Oct 2022 - Dec 2022

• Analyzed carbon price volatility in four Chinese carbon markets using GARCH models, demonstrating the limitations of conventional volatility models in emerging carbon markets.

• Investigated relationships between carbon prices, energy stocks, and energy prices through cointegration tests and VAR modeling. SKILLS

Python Packages: PyTorch, scikit-Learn, Matplotlib, Seaborn, statsmodels, pandas, NumPy. Others: Tableau, AWS (Amazon Web Services), CRM systems.

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