RICKY ZHENG

• Professional Summary

Highly motivated Math and Statistics major with a strong foundation in quantitative analysis, statistical modeling, and data-driven decision-making. Proven academic excellence and a keen interest in financial analysis. Seeking opportunities to leverage analytical skills and financial knowledge in a challenging position, with the long-term goal of becoming a Chief Financial Analyst.

Rutgers University-New Brunswick
Bachelor of Science in Mathematics and Statistics
Expected Graduation: 2026

• GPA: 3.3
• Relevant Coursework: Probability Theory, Financial Mathematics, Data Analysis, Econometrics, Linear Algebra, Statistical Computing

Intern - Arch Auto

• Assisted in data analysis and financial reporting for various departments, focusing on performance metrics and profitability analysis.
• Developed statistical models to forecast sales trends, optimizing inventory management and reducing costs by 15%.
• Collaborated with senior analysts to prepare monthly financial statements and projections, enhancing reporting accuracy by 20%.

Research Assistant
Rutgers University, Department of Mathematics and Statistics

• Conducted research on statistical methodologies and their application in financial modeling.
• Analyzed large datasets using R and Python, identifying key insights that contributed to a published paper on financial risk analysis.
• Presented findings to faculty and peers, demonstrating strong communication and analytical skills.
• Technical Skills: R, Python, SQL, MATLAB, Microsoft Excel (Advanced), Power BI
• Financial Analysis: Financial forecasting, portfolio optimization, cost-benefit analysis, risk assessment
• Quantitative Skills: Statistical modeling, probability theory, hypothesis testing
• Soft Skills: Strong communication, team collaboration, problem-solving, attention to detail

Financial Market Analysis Using Statistical Models

• Designed and implemented statistical models to analyze financial market data and predict stock price movements.
• Utilized R and Python for data cleaning, visualization, and hypothesis testing, achieving a prediction accuracy of 85%.

Sales Forecasting Model for Arch Auto

• Developed a forecasting model using linear regression and time-series analysis, accurately predicting monthly sales and informing strategic decisions.
• Reduced forecast error by 30% compared to previous methods used.
• Financial Modeling & Valuation Analyst (FMVA) – Corporate Finance Institute
• Python for Data Science and Machine Learning – Coursera