Open to Work M.A. Statistics @ UC Berkeley

// Hello, world! I'm

Shizhe
Zhang

|

A Psyduck from UC Berkeley 🐥 — waddling through data, building ML models, and occasionally suffering from a statistical headache. Passionate about turning messy numbers into beautiful insights.

4.0Current GPA
3.96Undergrad GPA

About Me

I'm a first-year M.A. Statistics student at UC Berkeley, with a deep interest in the intersection of statistical modeling, machine learning, and quantitative finance. My academic journey began at Zhejiang University where I graduated with honors in Economics (Advanced Class).

During internships at leading Chinese financial institutions, I applied gradient-boosting models and network analysis to build alpha-generating strategies and equity research pipelines. I thrive at turning raw, messy data into rigorous, interpretable models.

Outside of research, I served as President of the League of Economics School at Zhejiang University, organizing academic events and fostering a community of 500+ students.

🐥
Nickname
Psyduck @ UC Berkeley
📍
Location
Berkeley, California
🏆
Chu Kochen Honors
Top 1.3%
💼
Target Role
Data Science & ML

Skills & Technologies

⌨️

Languages

PythonRSQL MatlabBashLaTeX
Python95%
R85%
SQL80%
🤖

ML / AI

Machine LearningDeep Learning NLPRAG LightGBMXGBoost
Machine Learning90%
Deep Learning82%
LLMs / RAG85%
🛠️

Tools & Other

GitVimLinux/BashData Structure Quant FinancePortfolio Opt.
Git / DevTools88%
Quant Finance85%
Research92%

Experience

Quantitative Researcher

Guotai Haitong Securites

Jun – Aug 2025
  • Engineered event-driven alpha strategies leveraging LightGBM on historical price and corporate event data, improving factor IC.
  • Applied network analysis to model inter-stock relationships for factor research, uncovering latent market structure patterns.
  • Collaborated with senior quants to backtest and validate strategies within a proprietary research framework.
LightGBMNetwork AnalysisAlpha ResearchPython

Research Assistant

SDIC Securities

Jun – Aug 2024
  • Designed and maintained ETL pipelines to consolidate financial data from multiple sources, reducing data processing time significantly.
  • Built an XGBoost classification model for equity return prediction, supporting analyst coverage decisions.
  • Produced research reports synthesizing model outputs with fundamental analysis for investment committee review.
XGBoostETL PipelinesEquity ResearchSQL

President

League of Economics School, Zhejiang University

Jun 2023 – Jun 2024
  • Led a student organization of 500+ members, overseeing academic lectures, career development events, and cross-department collaborations.
  • Organized 10+ high-profile events including industry talks with alumni from top financial institutions.
  • Mentored underclassmen on research skills, internship preparation, and academic planning.
LeadershipEvent ManagementMentorship

Featured Projects

🔍
Industry Partner: Pyramyd

RAG-Driven Company Search System

Built a production-ready Retrieval-Augmented Generation pipeline that enables intelligent company discovery by semantically searching and ranking firms based on complex natural-language queries. Integrated vector embeddings, document store, and LLM-based summarization.

RAGLLMsNLPSearchRecommendation
📈

Robust Portfolio Optimization of CNE5 Factors

Applied robust optimization methods — including worst-case and distributionally robust formulations — to Chinese equity (CNE5) factor portfolios. Investigated how parameter uncertainty propagates into portfolio weights and risk-adjusted returns.

Portfolio OptimizationRobust MethodsQuant FinancePythonR
🔬

Capital Market, Rational Inattention & Internet Search

Empirical research examining how investor limited attention — proxied through internet search volume indices — affects asset pricing in capital markets. Constructed panel datasets linking search trends to stock-level return anomalies.

EconometricsPanel DataAsset PricingPythonQuantitative Investment

Latest Blogs

March 4, 2026

Equilibrium Strategies in the Continuous Yankee Swap

A rigorous game-theoretic analysis of sequential allocation mechanisms, exploring backward induction and optimal stealing heuristics in a continuous uniform distribution.

December 18, 2025

STAT 201B: Advanced Statistics Notes

A comprehensive set of study notes for STAT 201B at UC Berkeley, covering Bootstrap, MLE, Bayesian inference, and decision theory.

Education

M.A. Statistics

University of California, Berkeley

Aug 2025 – Dec 2026
GPA4.0 / 4.0

Focusing on statistical theory, machine learning methodology, and applied probability. Engaged in research at the intersection of statistics and data science.

Statistical TheoryMachine LearningApplied Probability

B.S. Economics (Advanced Class)

Zhejiang University

Aug 2021 – Jun 2025
GPA3.96 / 4.0

Enrolled in the selective Advanced Class program. Graduated as an Outstanding Graduate with multiple top-tier scholarships.

🏆Certificate of the Chu Kochen Honors Program (Top 1.3%)
🌟Outstanding Graduate
🥇First Prize Scholarships (Multiple)

Get In Touch

I'm actively looking for data science, machine learning, and quantitative research roles. Whether you have a full-time opportunity, an internship, or just want to chat about interesting problems — my inbox is always open.

Say Hello