Finance professional pursuing my Master of Science in Financial Analytics at California State University, Long Beach, with an expected graduation of August 2026. CFA Level I candidate with a strong interest in asset management, investment research, and market-driven decision-making.
My background combines client-facing banking and branch operations at JPMorgan Chase — internal controls, cash management, operational compliance — with quantitative financial modeling and academic work in fixed income, derivatives pricing, machine learning, and valuation.
I bring analytical depth and an execution mindset — comfortable with financial statements, market data, and the tools that make research faster. FINRA SIE certified. Fluent in English and Vietnamese.
Coursework in fixed income, derivatives pricing, machine learning, and valuation. GPA 3.75.
Concentration in finance with quantitative methods. GPA 3.75.
Client-facing banking and branch operations: internal controls, cash management, operational compliance.
Python · Advanced Excel · Bloomberg Terminal.
A complete record of education, certifications, work history, and technical skills. Available as a PDF for quick viewing or an editable DOCX. Last updated June 2026.
Compresses the research workflow into one place: live market data, financial statements, self-computed valuation ratios, comparable-company analysis, options activity, insider trades, SEC filings, and news — from initial idea to underwriting in one interface.
The valuation layer handles edge cases explicitly: non-meaningful P/E, negative free cash flow in DCF, and accounting-driven ratio distortions. Output is usable in real analysis, not just visually impressive.
Analyzed Boeing's debt maturity schedule, leverage ratios, and interest coverage using Bloomberg, quantifying the credit risk premium embedded in bond yields relative to Treasuries. Forward-looking narrative on capital structure and refinancing risk.
Built a Long Short-Term Memory (LSTM) neural network in Python to forecast Walmart (WMT) stock prices using historical market data. Evaluated with RMSE; visualized predicted vs. actual to assess accuracy and trend-following behavior.
Modeled asset price dynamics using Geometric Brownian Motion (GBM) to simulate thousands of price paths and estimate option payoffs. Validated outcomes under risk-neutral pricing.
Developed advanced spreadsheet models for financial statement analysis, ratio benchmarking, and cash flow forecasting. Produced DCF valuation scenarios under base, optimistic, and downside cases.
Actively pursuing opportunities in asset management, investment research, and quantitative finance. If you're looking for someone who combines market judgment, analytical rigor, and strong execution — let's talk.