Sihan Chen

Business and Economics double major with a minor in Computer Science at Brandeis University. Strong analytical and problem-solving skills with hands-on experience in financial analysis, market research, and data-driven decision-making. Adept at translating complex data into strategic insights to drive business growth and operational efficiency. Highly adaptable and detail-oriented, with a proven ability to collaborate in dynamic team environments and deliver results under pressure.

• Google Ads Search Certificate (In Progress, Expected March 2025)
• Google Data Analytics Professional Certificate (In Progress, Expected June 2025)

Financial Analysis of Nike & Under Armour

• Conducted a comprehensive financial analysis of Nike & Under Armour, evaluating 4 years of financial data (2020-2023).
• Utilized Excel-based financial models to analyze key financial ratios (ROE, Net Profit Margin, Debt-to-Equity, Inventory Turnover) and industry benchmarks.
• Assessed Nike’s stronger profitability ( ROE 35% vs. 21%(UA) ), while identifying UA’s post-pandemic recovery trends.
• Provided investment recommendations based on profitability trends and market positioning.

Tesla Inc. Strategic Business & Financial Analysis

• Conducted a comprehensive business analysis of Tesla Inc. for a Fortune 500 consulting project.
• Utilized FactSet, IBISWorld, Statista, and SEC filings to assess market trends, financial health, and competitive positioning.
• Analyzed key financial metrics (ROE 17.66%, ROA 8.23%, Net Profit Margin 7.76%) and developed strategic recommendations on cost optimization, product diversification, and market expansion.
• Evaluated Tesla’s direct-to-consumer model, supply chain efficiency, and renewable energy initiatives.

Pharmaceutical Biotech Industry: Financial & Data Analysis

• Conducted financial and market analysis of leading pharmaceutical biotechnology firms (Pfizer, Gilead, Johnson & Johnson) using FactSet, Statista, and Mergent Online.
• Built Excel-based financial models to perform Scenario Analysis, forecasting Net Income and EBITDA trends under varying R&D and legal claim expense scenarios.
• Applied data visualization techniques (Heat Maps, Trend Analysis) to highlight industry R&D spending trends and stock market performance.
• Provided data-driven strategic recommendations, including cost optimization, AI-driven diagnostics, and market expansion strategies.