Hey there 👋

I'm Michael Li

Financial Planning & Analysis

Columbia University · M.A. in Quantitative Methods in the Social Sciences · Graduating Dec 2026

I'm a Columbia University M.A. candidate in Quantitative Methods in the Social Sciences, with a B.A. in Computer Science and Economics from Boston University. My focus is FP&A: budgeting, rolling forecasts, P&L and variance analysis, and scenario and sensitivity modeling that show what drives business performance and support better decisions. I've built this through internships in private equity, a search fund, investment banking and fixed income, where I worked on financial models, valuation, operating budgets and management reporting. I combine finance with data skills in Excel, VBA, Power BI, SQL and Python to turn numbers into clear insights.

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Experience

Investment Analyst Intern (Private Equity) · 3Q Investment Partners · Apr 2026 – Sep 2026
Investment Analyst Intern (Search Fund) · Ionian Pine Partners · Apr 2026 – May 2026
Investment Banking Summer Analyst · CICC · May 2024 – Jun 2024
Fixed Income Summer Analyst · Haitong Securities · Jul 2023 – Aug 2023

Education

Columbia University · M.A. in Quantitative Methods in the Social Sciences · Dec 2026
Boston University · B.A. in Computer Science & Economics · 2025

Skills

FP&A · Financial Modeling · Excel/VBA · Power BI · SQL · Python · Bloomberg · AI tools & agentic workflows (Codex, Claude Code, ChatGPT, Grok Bot) · Prompt engineering.

Selected analytical projects

Projects in time-series forecasting and customer analysis that complement my finance experience.

SEC Financial Data Infrastructure - KPMG Practicum
In progress

An ongoing Columbia QMSS practicum building SEC 10-K/10-Q data infrastructure. I own database and integration work, with a PostgreSQL foundation and a partial manual sample for future RAG/GraphRAG research.

Wave Height Prediction — Surf Vacation Planner
Forecasting

A time-series forecasting app that predicts ocean wave heights using Facebook Prophet and NOAA buoy data, helping surfers find optimal locations and dates for their next trip.

Predicting Customer Churn Using KNN
Customer Analytics

A Kaggle project using K-nearest neighbors to predict customer churn, exploring a business question relevant to customer retention and revenue planning.

View all projects →

How I use AI

I'm always staying on top of AI and exploring new ways to improve my workflow with it, from Codex, Claude Code and Grok Bot to Meta Muse, OpenClaw, Hermes, ChatGPT Dots, Granola and more. I'm building AI-powered workflows that help me and my team work smarter, and I'm always learning. Happy to chat about AI with anyone!

AI Usage

Codex has this token counter, so here's mine. Just something cool to show 😄

ChatGPT token summary and daily activity for @sharkml

Last updated: Nov 15, 2026

https://chatgpt.com/u/sharkml