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.
technical_stack = {
'programming_languages': ['Python', 'R'],
'data_manipulation': {
'sql': ['Oracle', 'PostgreSQL', 'SQLite']
},
'cloud_platform': ['AWS'],
'core_skills': {
'statistics': ['Causal Inference', 'Bayesian Statistics'],
'machine_learning': ['Regression', 'Tree-Based Models', 'Boosting']
}
}-
SMS Spam Detection System (Ongoing)
- Currently building a machine learning pipeline to classify SMS spam messages using Python, focusing on robust text classification techniques.
-
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.
-
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.
-
- Explored diverse data science concepts through projects accompanying my published Medium articles, focusing on practical applications and storytelling.