Computer Science & Mathematics @ Columbia University
Machine learning for finance · Quantitative research · Software engineering

Quantitative Researcher & Trader — D. E. Shaw · IBK Securities · NH Hedge Asset Management · May 2027 – Aug 2027
_{Summer Internship · Offer Received}

• Will design systematic quantitative strategies for market analysis — engineering alpha signals from price, order-flow, volatility and fundamental data, and validating them with leak-free walk-forward backtests, transaction-cost modeling and factor-level risk attribution
• Will build investment logic supporting proprietary trading — turning research into rule-based entry / exit, position-sizing and risk-limit frameworks, and monitoring live P&L, exposures and regime shifts to iterate on models in production

Software Engineer — Extriver Partners · May 2026 – Present

• Analyzed audiences of creator partners (18M / 2M / 100K Instagram, 500K YouTube) to size demand and product fit
• Led product management and development of creator-facing AI products and the company's internal workspace
• Tracked software unit economics, cut LLM costs with token budgets, usage quotas and caching, and monitored production performance

Data Science Intern — Paratus Investment · Seoul · Feb 2025 – Aug 2025
_{Reference & Recommendation: JungYeon (Andy) Kim, Managing Director}

• Screened 24 private-company targets using Capital IQ and 160+ listed peers; built LTM / NTM EV/Revenue, EV/EBITDA and P/E comp sets with growth, margin and size adjustments
• Automated peer selection, multiple refreshes and EV-to-equity bridges in Excel / xlwings / Python — ~40% fewer manual model updates
• Built five-year FCFF / DCF cases with WACC, terminal-growth and exit-multiple methods; analyzed revenue, EBIT margin, CapEx and NWC sensitivities for transaction pricing

Private Equity Analyst/Data Science Intern — Yuanta Investment · Seoul · Oct 2024 – Feb 2025

• Valued private companies using 10–15 relevant public peers, normalized EBITDA and trading multiples; supported valuation exhibits and investment committee (IC) reports
• Built operating and LBO models for prospective investments, stress-testing entry / exit EV/EBITDA, debt paydown, leverage and sponsor IRR / MOIC under base and downside cases
• Assessed Sunbo Industrial bolt-on targets, pro forma EBITDA and synergies; automated daily deal / industry news clipping and EML-based macro signals for portfolio review

FA Deal General Intern — Deloitte Korea · Seoul · Jan 2023 – Feb 2023
_{Reference & Recommendation: Sang-wook Nam, Managing Partner, Financial Advisory}

• Supported buy-side medical-device M&A diligence, analyzing revenue concentration, normalized EBITDA, working-capital movement and cash-flow conversion
• Prepared peer screening and target comparisons; identified acquisition candidates with potential commercial synergies, financial risks and integration considerations

Private Equity Analyst Intern — Paratus Investment · Seoul · Jun 2022 – Sep 2022

• Built manufacturing-sector DCF models linking volume, pricing, margins, CapEx and NWC to FCFF, discounted terminal value and implied equity value
• Standardized Excel valuation templates and automated research / market-news collection to update peer multiples, assumptions and deal-monitoring inputs

Researcher — Fact-based Economic Network (경제지식네트워크) · Seoul · 2022
_{With Y. Min & K. Ireh · presented at the Fact-based Economic Network}

• Researched the practical effectiveness of proprietary-trading quant strategies in the Korean market
• Analyzed why market-making strategies struggle to work in Korea, looking at the market structure and regulatory constraints they face
• Studied the problems of Korea's inheritance-tax system and presented Korea Inheritance Tax Story

Undergraduate Researcher — University of Waterloo · Waterloo, ON

• Researched how machine-learning models are evaluated — validation design, out-of-sample testing and the metrics used to compare models

Invited Guest Researcher — Financial Academy · Seoul · 2022

• Invited as a guest to research financial-crisis regimes through past financial crises, and how AI can recognize and respond to crisis regimes in markets

🧰 Also working with

_{C++  ·  Rust  ·  OCaml  ·  R  ·  SQL  ·  Shell}

Track Record 📈 Five years of my own broker-verified trading: ₩65.9M → ₩241.9M of total value ($49.3K → $181.1K) · 3.67× MOIC — compounding at 34.3% a year time-weighted (32.1% IRR) versus 15.1% for the KOSPI and 14.8% for the S&P 500, a +19.2 pp annual edge and +22.4% Jensen's alpha. ₩176.0M total profit with an 87% hit rate, 12.6× profit factor, Sharpe 0.94 / Sortino 2.20 and only 12 bp all-in trading cost; best trade +337% (HD Hyundai Heavy Industries). Every won reconciles to the Kiwoom statements, published in Korean and English. _{🧰 Python · pdfplumber · pikepdf · openpyxl · TWR / Modified Dietz · XIRR · Sharpe / Sortino / Jensen α · KOSPI · S&P 500 · Nasdaq-100 benchmarks}

Automated-DCF-ML
Engineers SEC Company Facts / XBRL data and fits Ridge & Elastic Net forecasts for six value drivers (revenue growth, EBIT margin, tax, D&A, CapEx, NWC intensity); converts them to NOPAT and FCFF, then a DCF to enterprise / equity value and fair value per share. Chronological training (through 2018) and testing (2022+).
_{🧰 Python · scikit-learn · SciPy}

InsightStream ⭐
DigitalOcean Gradient™ AI Hackathon — AI observability platform that streams logs through Kafka and uses Llama 3 to detect anomalies and summarize incidents in real time.
_{🧰 Kotlin · Spring Boot · Kafka · Next.js}

Revenue Dip Lab
Backtests buying companies with resilient revenue after sharp price drawdowns — five-panel research workspace, 3D CAGR surface sweeps and out-of-sample factor search on SEC EDGAR + Yahoo Finance data.
_{🧰 Python · FastAPI · JavaScript · Web Workers · SQLite}

Signals to Alpha
Research program turning real-economy signals into testable alpha factors — a U.S. K-Food alternative-data factor model with point-in-time signals, placebo tests and bias audits.
_{🧰 Python · statsmodels · SciPy · Jupyter}

MIDAS Terminal
Automated equity research terminal — ticker → market data → SEC EDGAR filings → financial analysis → peer comparison → rule-based catalysts & risks, exported as English / Korean Word research reports; async fetching with single-flight TTL caching and rate limiting.
_{🧰 Python · FastAPI · JavaScript · Plotly · SQLite · SEC EDGAR}

Nanny Mira — Child Temperament AI
Parent-reported child temperament web app in 4 languages (KO / EN / RU / PT-BR): an age-adapted 28-question assessment, 40 expandable analysis cards and DeepSeek LLM parenting guidance grounded with PubMed references; Prodamus card checkout.
_{Represented by: Илона Масельскене, Russia partner
🧰 Node.js · DeepSeek API · Low-Cost LLM Inference · RAG · Prompt Optimization · Context Caching · Token Budgeting · Usage Quotas}

Superdupercatai
AI comics & animation channel — AI-generated content production, growth and monetization analytics (70K followers, 20M peak views, ~1M average views / video).
_{🧰 Generative AI · content analytics}

Extriver Partners
Product & business modeling — creator audience geography, engagement and sector demand to evaluate vertical-software concepts; subscription, conversion and revenue-share scenarios; internal partner pipeline and research-to-execution workspace. Distribution tested through an owned short-form account (70K followers, 20M peak views, ~1M average views / video).
_{Partners: LoveSoo, TikTok · YouTube · Linktree  ·  Stick Stories  ·  Илона Масельскене  ·  Superdupercatai  ·  틱톡★꽐루  ·  Bushra  ·  BTS BORA WORLD (보라TV), TikTok  ·  Tushar Shetty, YouTube · Facebook
🧰 Node.js · Socket.io · Cloudflare R2}

🔬 Modeling libraries

📐 ML models

🤖 LLMs & AI engineering

📈 Financial data

⚙️ MLOps & data

🧩 Application stack

• 📐 Regularized regression — Ridge / Lasso / Elastic Net with CV, Pipeline + StandardScaler
• ⏱️ Leak-free validation — Chronological training and out-of-period testing to avoid look-ahead bias
• 📊 Statistical testing — OLS with statsmodels, Spearman / Pearson correlation, curve fitting with scipy.optimize
• 🧮 Factor models — Alternative-data signals as equity factors; multi-factor strategy fitting and backtesting
• 🛰️ LLM applications — RAG pipelines with vector search, LoRA / PEFT fine-tuning, real-time anomaly detection and research-grounded guidance
• 💹 Finance — DCF / FCFF · public comps · 3-statement & LBO · M&A diligence · EV-to-equity bridges

Bachelor of Computer Science – Mathematics · Department of Mathematics
<sub>🎓 Minor in Statistics
📍 New York, NY  ·  🗓️ 2026 – Present
🏛️ Clubs & Societies: KIGS — Finance Executive  ·  K-Quant

Relevant coursework</sub>

Bachelor of Computer Science · Cheriton School of Computer Science
<sub>🎓 Minors in Combinatorics & Optimization and Economics
📍 Ontario, Canada  ·  🗓️ Sep 2024 – Sep 2026
Reference & Recommendation: Tammy Schirle, Professor of Economics, Wilfrid Laurier University  ·  James Read, Chair of Industrial Design, Massachusetts College of Art and Design
🏛️ Clubs & Societies: Waterloo Quant Group (WQC)  ·  SIG

Relevant coursework










🎯 Combined GPA 3.53 / 4.00 (self-calculated)  ·  ➕ External coursework 19 credits (UMass Global 13, BYU 6)</sub>