This is

Vaishnavi.

Financial Analyst • FP&A • Valuation

Ask Vaishnavi

About Vaishnavi

Hi, I'm Vaishnavi Reddy, a financial analyst with a strong interest in FP&A, valuation, and financial analytics. I hold a Master's degree in Finance from the University of Massachusetts Boston and enjoy working at the intersection of finance and data, where structured analysis supports sound business and strategic decisions.

I focus on building practical, end-to-end finance tools using Excel, Python, SQL, and Tableau, including budgeting and forecasting models, variance analysis, and performance dashboards. Now, I'm looking to bring this blend of technical skill, analytical thinking, and business sense to teams working in financial analytics, data-driven strategy, or innovation-focused environments, especially where data and technology create meaningful impact.

Want to see how I work?

"Run the Quarter"

An FP&A Decision Simulation — Step into Vaishnavi's role and make decisions using imperfect data, tradeoffs, and real business pressure. See how your judgment compares to hers.

Phase 1 of 5

Resumé

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Certifications

CFA Program Level - 1

Qualified

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Financial Modeling & Valuation Analyst

(FMVA®)

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Projects

Equity Research & Analysis

NextEra Energy (CAPSTONE PROJECT)

Conducted a full equity research analysis, developing a BUY recommendation supported by a detailed review of business fundamentals, long-term growth drivers, and valuation-based insights.
Built a 5-year forward DCF model in Excel with three valuation scenarios, estimating intrinsic value and assessing sensitivity to revenue growth, margins, and cost of capital.
Analyzed 6+ years of financial statements and operating metrics, focusing on cash-flow generation, and capital structure

Market Sentiment Valuation

Designed a structured research framework to analyze how market sentiment impacts valuation multiples across 8-10 publicly listed companies, comparing behavior across different market regimes.
Extracted, cleaned, and organized 50k+ rows of financial, pricing, and market data using SQL, enabling consistent cross-company analysis.
Used Python (pandas, NumPy) to compute 15-20 key valuation and performance metrics (P/E, EV/EBITDA, margin trends, return measures) and quantify valuation dispersion under varying sentiment conditions.

Financial Modeling: Starbucks Corp

Built a multi-year financial model for a new Starbucks wellness beverage, forecasting revenue, costs, and cash flows across a 10-year horizon.
Analyzed pricing, operating margins (~15%), and launch investment assumptions to evaluate product-level profitability and scalability.
Performed scenario and sensitivity analysis (base, upside, downside) to assess financial viability, including NPV and IRR outcomes under different adoption rates.