I'm Nayeon, a Data Scientist with a solid foundation in Statistics and hands-on experience as a Statistical Analyst in the government sector. I excel at leveraging data-driven insights to drive impactful decisions.
- Programming Languages: Python, R
- Data Manipulation: SQL (Oracle, PostgreSQL, SQLite)
- Cloud Platform: AWS
- Statistics: Causal Inference, Bayesian Statistics
- Machine Learning: Regression, Tree-Based Models, Boosting
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SMS Spam Detection System (Ongoing)
- Currently building a machine learning pipeline to classify SMS spam messages using Python, focusing on robust text classification techniques.
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Causal Effect of Urban Parks on Children's Happiness
- Investigated the causal impact of urban park size on children's happiness using propensity score methods, uncovering valuable insights for urban planning.
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Small and Medium-sized Enterprises (SMEs) Closure Prediction Project
- Developed machine learning models in R using RandomForest, CatBoost, and BART to predict SME closures, with CatBoost achieving the highest F1 score of 0.992.
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- Explored diverse data science concepts through projects accompanying my published Medium articles, focusing on practical applications and storytelling.