HanJeong Ki
Data Scientist
Seodaemun-gu
Overview
5
5
years of professional experience
7
7
years of post-secondary education
Work History
GEMS Spatio-temporal Mean-field Algorithms
07.2023 - 02.2024
- Implement a spatio-temporal analysis algorithm by preprocessing satellite observation data
- For the development of standardized quality indicators, the quality flag is used as an index of idw to derive accuracy improvements
2023 Yonsei Big Data Analysis Competition
07.2023 - 08.2023
- By analyzing consumption patterns and store visit data, we apply a deep learning model GETNext to establish an optimal store placement plan.
Improve the Recommendation System Model
03.2023 - 06.2023
- Apply multiple recommendation models by analyzing Amazon book-crossing data
- Among several application models, a high-accuracy model is proposed by applying the diffusion recommender system, a generative deep learning model
Implementation of a Win Rate Prediction Model
06.2020 - 08.2020
- Establish a model that predicts the winning rate using KBO team data, analyze each team's statistics, and present strategies for improving the winning rate
Analysis of the Death Factors of Coronavirus
03.2020 - 06.2020
- Applying a competitive risk model to COVID-19 patient data to classify death and recovery factors, and predicting the cycle according to each factor
Developing a Model for Business Loan Approval
10.2019 - 12.2019
- Analyzing financial data to develop machine learning models necessary for loan approval decisions
- Analysis of variable importance for loan risk assessment
New York City Airbnb Price Forecast
10.2019 - 12.2019
- New York City Airbnb Price Forecast Using Accommodation Data
- Fit multiple machine learning models and tune superparameters to increase prediction rate
Lalabla's Demand Forecast Model
07.2019 - 08.2019
- Integrating weather and sales data to build Lalavla's demand forecasting model
- Propose product promotion and inventory management strategies through text crawling with family keyword search
Propose a new rating formation and recommendation
02.2019 - 03.2019
- New rating formation and recommendation system suggestions from yelp, improved user satisfaction, and business insights through review data analysis
Education
Master of Arts - Statistics
Yonsei University, South Korea
Seoul, South Korea 09.2022 - 08.2024
Bachelor of Science - Statistics
Sookmyung Women University, South Korea
Seoul 03.2016 - 02.2021
Skills
Python, R
Accomplishments
- Weather Big Data Contest (Excellence Award), Korea Meteorological Administration, August 8, 2019
- Yonsei Big Data Competition (Best Award), Yonsei University, August 25, 2023
- R Shiny Application Development Contest (Best Award), Yonsei University, February 17, 2023
Timeline
GEMS Spatio-temporal Mean-field Algorithms
07.2023 - 02.2024
2023 Yonsei Big Data Analysis Competition
07.2023 - 08.2023
Improve the Recommendation System Model
03.2023 - 06.2023
Master of Arts - Statistics
Yonsei University, South Korea
09.2022 - 08.2024
Implementation of a Win Rate Prediction Model
06.2020 - 08.2020
Analysis of the Death Factors of Coronavirus
03.2020 - 06.2020
Developing a Model for Business Loan Approval
10.2019 - 12.2019
New York City Airbnb Price Forecast
10.2019 - 12.2019
Lalabla's Demand Forecast Model
07.2019 - 08.2019
Propose a new rating formation and recommendation
02.2019 - 03.2019
Bachelor of Science - Statistics
Sookmyung Women University, South Korea
03.2016 - 02.2021
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