DATA RESEARCHER · SEOUL, KR
I help people understand data and AI — not just how they work, but what they make possible.
Research.
Reason.
Results.
My work connects research, analytics, and applied AI to make complex ideas clearer, more practical, and easier to act on.
Hana Cho
About
With eleven years of experience as a math teacher and a long-standing interest in programming, I moved into the world of big data and AI with a strong focus on meaningful application.
As an AI engineering instructor and data insight consultant, I specialize in machine learning education, generative AI, and practical AI use cases that professionals can apply in real work settings.
My work sits at the intersection of education, product, and research. I enjoy translating technical ideas into language, systems, and decisions that people can actually use.
Through experience spanning Airbnb, a logistics startup, and an AI bootcamp environment, I have come to believe that data is not just for machines. It is for people seeking clarity, confidence, and action.
Projects
Project 01
Incheon Tourism Analytics
Built an analytics-ready tourism data model for Incheon using dbt and BigQuery, with spatial analysis connecting tourism spots and nearby accommodation.
dbt · BigQuery · Data Studio
View on GitHub ↗Project 02
Room Occupancy: Time-Aware Evaluation
Evaluated room occupancy classification using environmental sensor data, comparing random and chronological train-test splits to examine how time-aware evaluation affects model performance.
Python · pandas · scikit-learn · Random Forest
View on GitHub ↗Project 03
German Credit: Cost-Aware Classification
Explored credit risk classification using logistic regression, comparing the default decision threshold with a cost-aware threshold to examine how asymmetric misclassification costs affect decisions.
Python · pandas · scikit-learn · Logistic Regression
View on GitHub ↗Project 04
Olist Customer Satisfaction: Delivery Feature Modeling
Modeled customer dissatisfaction using real e-commerce delivery data, comparing absolute delivery time and delivery expectation gap to examine how feature representation affects classification performance.
Python · pandas · scikit-learn · Logistic Regression
View on GitHub ↗Teaching & Advisory
2026 Feb - Mar
AI Advisory & Executive Consulting
Delivered AI tool adoption and workflow automation education for Data Spring Korea, alongside executive consulting focused on practical business use.
2025 Apr - Current
AI & Data Education
Designed and delivered education in Python, machine learning, and data analysis, supported by mentoring, code feedback, and learner-centered guidance.
2025 Mar - Current
Public Lecture
Delivered public lectures on AI-assisted data analysis, reaching more than 700 participants across professional audiences.
2024 Jun - Current
Instruction & Mentoring
Led live coding, project review, model evaluation, and technical guidance so that learning could connect directly to practical implementation.