About Me
Professional Background
I'm Youngmin Ju, a seasoned Data Scientist and Economist with extensive experience in developing and optimizing data-driven solutions, focusing on experimentation and causal inference. As the founder of a research-driven organization, I've successfully led cross-functional projects, delivering business impact through data strategy and technical execution.
My expertise lies in enhancing decision-making processes, statistical analysis, and A/B testing, with demonstrated success in improving CRM performance and data processing efficiency. Throughout my career, I've worked with organizations across various industries, helping them leverage data to make informed decisions and drive business growth.
My approach combines rigorous statistical analysis with creative problem-solving, always keeping the end goal in mind: delivering insights that create value and drive positive change.
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, 2021
Dissertation: "Essays on Causal Inference (Affirmative Action in Korea - Regression Discontinuity with Multiple Assignment Variables)"
M.A. in Economics
Korea University, 2010
Honors: Brain Korea 21 scholarship
B.S. in Mathematical Sciences
Korea Advanced Institute of Science and Technology (KAIST), 2008
Honors: Mathematical Science Department scholarship | National Science and Technology scholarship
Professional Experience
Founder / Data Scientist
Oct. 2021 - PresentDecode Data Inc.
- Founded and led a nonprofit research initiative focused on data science applications in economics and business decision-making
- Directed all stages of project development, from ideation to deployment, combining domain expertise with technical execution
- Oversaw stakeholder engagement, data strategy, and infrastructure planning, establishing a scalable foundation for future data-driven research
Data Scientist
Oct. 2022 - Mar. 2024Datacrunch Global
- Led the design and deployment of Business Decision Solutions (BDS) for E-commerce company by integrating order, procurement, settlement, and inventory data, which enables a 30% reduction in decision-making time
- Designed and implemented machine learning models for demand forecasting, optimizing procurement decisions and reducing excess inventory costs by 15-20%
- Led the project to automate data cleansing processes, reducing manual report generation time by 80%
Assistant Professor (First Lieutenant)
Jun. 2010 - May. 2013Korea Army Academy at Yeongcheon
- Led cadets in the Economics department, achieving #1 ranking for 2 consecutive years
- Developed robust Panel Data economic models for two government research projects
Economics Researcher
Oct. 2009 - Mar. 2010Korea University – Client: Hyundai MOBIS
- Applied causal inference techniques (Difference-in-Differences, Before-After) to assess the economic impact of Hyundai Mobis' alleged anti-competitive behavior
- Proved that penalties imposed on relayers had no statistically significant negative effect on sales, resulting in a $120 million reduction in fine
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
Led a government research project to design robust economic models for estimating optimal national defense R&D expenditure and efficient management, contributing to a larger 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
Conducted comprehensive research on defense R&D expenditure optimization and management efficiency, providing evidence-based recommendations for resource allocation in national defense.
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.