About Me
Professional Background
As Sr. Manager, Program Management at Coupang, I lead the Business Operations team for Rocket Growth Consumables — the operational excellence function for the entire 2P Consumables business, turning manual, reactive work into standardized, proactive mechanisms. Recent work includes fee-scenario analysis that weighs seller and platform economics together, a seller-level P&L simulator that pinpoints each seller's heaviest cost, and a weekly reporting structure and shared analytics hub that put category, BD and finance teams on the same dashboards. I bring the causal inference I trained in as an Economics PhD (USC) to those operating decisions, so teams can settle what actually worked — in numbers, not opinions.
Alongside that, I co-run AIEconLab (인공지능경제연구소), a Korean research collective on the economics of AI that I co-founded with two fellow USC economics PhDs in 2023. Before Coupang I was AI Lead at VWS, where I designed an LLM + behavioral-ML recommendation pipeline for non-performing loan (NPL) recovery; recovery rates rose 1.2–1.3x and collection operating cost fell 15%. Earlier I founded Decode Data Inc., a US non-profit research corporation, and alongside it worked with Datacrunch Global as a client engagement, leading demand forecasting and moving an e-commerce recommender's success metric from CTR to long-term customer value. My work on causal identification for partly ordered treatments is published in the Oxford Bulletin of Economics and Statistics.
Skills & Expertise
Programming & Tools
- Python (NumPy, pandas, Scikit-Learn)
- R and STATA for statistical analysis
- SQL for database querying
- Git for version control
Machine Learning
- Classification & Regression
- Deep Learning (TensorFlow, PyTorch)
- Clustering & Dimensionality Reduction
- Time Series Analysis
Data Analysis
- Exploratory Data Analysis
- Feature Engineering
- Large-Scale ETL
- Data Visualization (matplotlib, seaborn, plotly)
Causal Inference
- Experimental Design & A/B Testing
- Regression Discontinuity
- Difference in Differences
- Instrumental Variables
Education
Ph.D. in Economics
University of Southern California, 2015 - 2021
Dissertation: "Essays on Causal Inference (Affirmative Action in Korea - Regression Discontinuity with Multiple Assignment Variables)"
M.A. in Economics
Korea University, 2008 - 2010
Honors: Brain Korea 21 scholarship
B.S. in Mathematical Sciences
Korea Advanced Institute of Science and Technology (KAIST), 2004 - 2008
Honors: Mathematical Science Department scholarship | National Science and Technology scholarship
Professional Experience
Sr. Manager, Program Management
Oct. 2026 - PresentCoupang (RG Consumables, Business Operations), Seoul, Korea
Leading the Business Operations team for Rocket Growth Consumables — the operational excellence function for the entire 2P Consumables business
- Issue Resolution & Standardization: Partner with Account Managers and cross-functional stakeholders to take operational issues from root-cause diagnosis to prevention design, converting manual, reactive work into standardized, proactive mechanisms
- Operational Handover: Transitioning the team's reporting and analytics tools to team-run operation through an operations manual and assigning an owner to each tool
Principal, Program Management
Jun. 2026 - Sep. 2026Coupang (RG Consumables), Seoul, Korea
Program manager for Rocket Growth Consumables — seller acquisition, fee and P&L structure analysis, GMV analysis, and operational reporting
- Seller Economics: Built fee-scenario analysis and a simulator that weigh seller payout and platform profitability together, and estimated scenario-level selection growth with Bass and logistic diffusion models; pilots were designed with success criteria agreed before launch
- AM Enablement: Built seller-level P&L simulations that locate cost bottlenecks across advertising, logistics, and FC fees, and standardized tailored conversion strategies into a form AMs apply directly
- Business Visibility: Launched a shared analytics hub and sub-category performance dashboards for weekly reporting and business-review shortfall analysis, plus a profitability dashboard for the monthly review
- Stack: SQL, Python, P&L simulation, Bass and logistic diffusion models, difference-in-differences, A/B testing, metrics framework design
Co-founder
Jun. 2023 - PresentAIEconLab (인공지능경제연구소), Korea (Remote) · Part-time
Co-founded with two fellow USC economics PhDs — a Korean research collective on the economics of AI
- Research Collective Leadership: Co-founded and run the collective — set research direction, manage publication operations, and hold editorial quality across a body of work now at 41 pieces in three tracks (AI columns, AI analysis, AI trends)
- Authored Research: Author 8 pieces — the causal inference & platform economics track, including how Amazon engineers its marketplace with economics (Double ML, causal forests) and what transfers to other marketplaces, and why Uber's delivery-density advantage stops at national borders, plus a working paper on AI adoption and occupational exposure in Korea
- Research Translation: Translate academic method into practitioner language — e.g. a five-zone diagnostic (input, context, retrieval, reasoning, execution) for locating where enterprise AI deployments actually break
AI Lead / Data Scientist
Jul. 2025 - May. 2026VWS, Seoul, Korea
Owned AI product strategy for NPL recovery end to end — problem framing, model design, deployment, and the operating metrics leadership reviews
- Recovery Recommendation Pipeline: Designed an LLM + behavioral-ML recommendation pipeline that ranks contact channel, timing and message per delinquent account, deployed across multiple B2B clients; debt-recovery rates rose 1.2–1.3x and collection operating cost fell 15%
- Causal Channel Measurement: Rebuilt the channel strategy by measuring true channel lift with causal inference (DID / uplift modeling) rather than raw response rates, retiring channels that showed no incremental effect
- Funnel Diagnostics: Found a hidden cause of falling funnel conversion by instrumenting stage-level KPI monitoring, isolating the failing step and giving operations a weekly read they act on directly
Data Scientist
Oct. 2022 - Mar. 2024Datacrunch Global, Seoul, Korea (Remote)
Concurrent client engagement while running Decode Data — data pipelines, demand forecasting and recommendation metrics
- Causal-Inference Based Forecasting: Developed a hybrid model combining statistical intervention analysis with Deep Learning (LSTM). Causally separated organic demand from promotion-driven spikes to minimize inventory risk and quantify marketing ROI
- Recommender Success Metric: Moved an e-commerce recommender's success metric from click-through rate (CTR) to long-term customer value (LTV), validated with cohort analysis and A/B tests
- Scalable ETL Architecture: Designed AWS-based pipelines processing over 3M daily e-commerce transactions. Optimized PySpark jobs to reduce processing time by 70% and ensured data integrity across heterogeneous systems (WMS/ERP)
- Automated Decision Support System: Built a Data Warehouse integrating fragmented order/inventory data and deployed real-time ordering recommendation APIs to enable data-driven decision-making
Founder / Data Scientist
Oct. 2021 - Jul. 2025Decode Data Inc., Los Angeles, USA
- Startup Leadership: Led the entire product lifecycle from ideation to development and team building, establishing an Agile organizational culture
- ALM Valuation Engine: Developed an Asset-Liability Management (ALM) engine implementing bootstrapping algorithms for yield curve derivation and risk-neutral approaches for fair value calculation
Assistant Professor
Jun. 2010 - May. 2013Korea Army Academy at Yeongcheon (KAAY), Yeongcheon, Korea
- Defense Econometrics: Led government research projects on defense R&D efficiency. Estimated optimal defense spending using panel data regression and published findings in academic journals
- Organizational Analysis: Analyzed the correlation between economic incentives and organizational effectiveness using large-scale survey data to improve personnel management
- Educational Excellence: Designed economics curriculum and implemented a quantitative academic performance evaluation system, achieving the top departmental ranking for two consecutive years
Economic Researcher
Mar. 2009 - Mar. 2010Korea University (Client: Hyundai Mobis), Seoul, Korea
- Regulatory Risk Mitigation: Contributed to saving approx. $120M in potential fines by econometrically modeling pricing mechanisms to prove compliance with fair trade regulations
- Causal Analysis for Antitrust: Utilized Difference-in-Differences (DID) to analyze the causal effect of corporate actions on market prices, providing logical grounds for antitrust defense
Publications
Control Function Approach for Partly Ordered Endogenous Treatments: Military Rank Premium in Wage
Oxford Bulletin of Economics and Statistics, June 2017
Developed a novel statistical methodology to analyze the effects of military ranks on post-service wages, addressing endogeneity in rank assignment through an innovative control function approach.
View PublicationA Study on Scale of Defense Expenditure for Security Menace: A Panel Regression Analysis Approach
Journal of Korea Army Academy at Yeong-cheon, 2013
Estimated the optimal scale of defense expenditure relative to security threats using panel data regression, contributing to a government research project with a total value exceeding $40,000.
Affirmative Action in Korea - Regression Discontinuity with Multiple Assignment Variables
Dissertation Research, 2021
Developed an identification method for fuzzy regression discontinuity design with multiple assignment variables to analyze affirmative action effects in Korea. Found that while the overall policy showed no significant effect, company size-based implementation increased female employment rates by 5 percentage points.
Store Item Demand Forecasting Project
Technical Report, 2021
Implemented a Recurrent Neural Network with Long Short-Term Memory (LSTM) using Keras/TensorFlow to predict 3-month item sales across different stores, supporting business planning and cash flow management. The LSTM model reduced error rates to 86% of traditional ARIMA forecasting methods.
Customer Churn Prediction Project
Technical Report, 2020
Built a multi-classification model using XGBoost to identify customers likely to churn and determine the most influential features. The XGBoost model achieved an AUC of 93.3%, outperforming other algorithms including GBM (90.89%), Random Forest (87.76%), and Decision Trees (83%).
Online Retail Customer Segmentation Analysis
Technical Report, 2020
Segmented and cleaned business performance metrics including monthly revenue, activation rate, retention rate, and churn rate. Applied Lifetime Value (LTV) methods to improve multi-classification model accuracy from 76.5% to 84%.
A Study on the Estimation of Optimal Defense R&D Expenditure and Efficient Management
Korea Army Academy at Yeongcheon, 2012
Led a government research project to design economic models for estimating optimal national defense R&D expenditure and efficient management, providing evidence-based recommendations for resource allocation and contributing to a larger project with a total value exceeding $40,000.
The Study on Scale of Defense Expenditure
Korea Army Academy at Yeongcheon, 2011
Analyzed defense expenditure patterns and requirements, developing models to determine appropriate funding levels based on security threats and national priorities.
Economic Effects of Alleged Anti-Competitive Behavior of Top Automobile Parts Company
Research Report for Hyundai MOBIS, 2010
Designed causal inference models to investigate economic effects of alleged anti-competitive behaviors on retail agencies, mediating companies, repair shops, and consumers. The research provided economic evidence that helped reduce the imposed fine from $150 million to $30 million.