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charveepat/README.md
╔══════════════════════════════════════════════════════════════╗
║              CHARVEE PATEL // FINANCIAL ANALYST              ║
║      FP&A · Financial Modeling · Applied AI for Finance      ║
╚══════════════════════════════════════════════════════════════╝

[*] Based in India · open to opportunities globally [@] charveepatel00@outlook.com [>>] LinkedIn · Live demo — SEC Variance Analyzer

>> SYSTEM STATS
> experience  : 4+ years — FP&A, financial modeling, decision support
> flagship    : built the investor model behind a $13.5M LP raise at a
>               15-person energy startup
> ownership   : owned $10–11M annual OpEx forecasting · modeled a
>               $22.3M facility NPV across three capital structures
> stack       : Python · SQL · Streamlit · SEC EDGAR · Claude API
> status      : open to FP&A · financial analyst · applied-AI-in-finance
>               · GTM / forward-deployed roles at finance & AI companies

>> FEATURED PROJECTS  (built in code — open and run them)
[+] SEC Variance Analyzer — live ↗
> what   : quarterly variance analysis on real SEC EDGAR filings for
           any US public company, with a grounded AI narrative
> design : the model only ever sees a pre-computed variance table —
           every figure it cites traces to a cell, never invented
> stack  : Python · Streamlit · SEC EDGAR XBRL · Claude API · Altair

[+] RAG Earnings Analyst
> what   : ask investment questions in plain English, get answers cited
           back to real earnings-call transcripts
> how    : FAISS + hybrid search (BM25 + dense) + HyDE + cross-encoder
           re-ranking · RAGAS-style faithfulness / precision scoring
> stack  : Python · sentence-transformers · FAISS · LangChain · Claude

[+] Position Reconciler
> what   : automates end-of-day price reconciliation between a portfolio
           management system and a custodian feed
> flags  : any position whose two sources diverge past tolerance is
           surfaced as a BREAK for review — a core investment-ops task
> stack  : Python · pandas

>> VALUATION & MODELING  (independent / academic — not code repos)
[~] M&A — confectionery buy-side + sell-side valuation
> $2.51B entry at 17.55x EBITDA · 5-year hold · 2.49x MOIC · 20.0% IRR
> DCF range $2.67B–$3.60B at 11.15% WACC · comps: Hershey, Mondelez
[~] Coca-Cola — FCFE intrinsic valuation
> $72.93 intrinsic vs $62.69 market · cost of equity blended across
  five methods · benchmarked vs PEP / KDP / MNST

>> EXPERIENCE
[>>] Financial Analyst @ Augustus Energy (Feb 2024 – Dec 2025)
> built the 7-year integrated P&L / CapEx / cash-flow model projecting an
  $84M–$114M revenue ramp · directly supported a $13.5M LP raise
> owned $10–11M annual OpEx budgeting · cut executive reporting time
  30% with Tableau + Excel dashboards for board review

[>>] Finance Intern @ PDEU Innovation & Incubation Centre (Sep 2020 – May 2022)
> cash-flow dashboards across 120+ early-stage startups · cut reporting
  lead time 30% · compliance work that unlocked ~$1.2M in grants

[>>] Financial Analyst @ Benchmark Agencies (Jan 2020 – Aug 2020)
> DCF/NPV feasibility that greenlit a new product line · automated
  monthly reporting in Excel · 25% prep-time reduction

>> SKILLS
analytics  : SQL · Python · R · Excel (Advanced) · Tableau · VBA
modeling   : DCF · NPV · IRR · LBO · scenario planning · forecasting
platforms  : Bloomberg · Capital IQ · FactSet · Morningstar
applied ai : RAG (FAISS · hybrid search · re-ranking) · agentic tool-use
             LLM grounding & evaluation · Claude API

>> EDUCATION
[^] M.S. Finance — Asset Management, Data Analytics · UIUC Gies · 2022–2023
[^] B.B.A. (Hons) Finance, Minor Economics · PDEU · 2018–2022

[@] reach me : charveepatel00@outlook.com [>>] connect : linkedin.com/in/charveejpatel

Pinned Loading

  1. sec-variance-analyzer sec-variance-analyzer Public

    Quarterly variance analysis on real SEC EDGAR filings for any US public company — Python + Streamlit, with a grounded AI narrative

    Python

  2. rag-earnings-analyst rag-earnings-analyst Public

    Ask investment questions, get answers grounded in real earnings-call transcripts — RAG (FAISS + hybrid search + HyDE + re-ranking) with source-cited answers

    Python