Hi, I'm Jimin, a data science practitioner and researcher focused on turning complex data into clear, actionable insights. I enjoy building reproducible analytics workflows, designing machine learning experiments, and communicating results that help teams make evidence-based decisions.
- Data science background spanning statistical analysis, machine learning, data visualization, and end-to-end analytics workflows.
- Research experience in framing data-driven questions, reviewing literature, designing experiments, validating results, and presenting findings clearly.
- Practical project experience across exploratory data analysis, predictive modeling, dashboarding, and applied AI/ML prototypes.
- Strong interest in responsible, interpretable, and human-centered data products.
| Project | Focus | Highlights |
|---|---|---|
| S&P 500 vs KOSPI Analysis | Financial data analysis, reproducible research | Compared monthly S&P 500 and KOSPI performance from 2000–2024, including returns, volatility, drawdowns, and rolling correlation. Built a reproducible Python workflow with committed data, automated verification, SVG visualizations, tests, and GitHub Actions. |
| 1D Ising Monte Carlo Simulation | C++, Monte Carlo simulation, computational physics | Implemented a reproducible Metropolis simulation of the one-dimensional Ising model using C++17, periodic boundaries, deterministic random seeds, independent chains, uncertainty estimates, and comparison with exact theoretical results. |
| ESG Analysis with GNNs | Graph neural networks, machine learning research | Investigated graph-based methods for ESG-related prediction, implemented and compared multiple modelling approaches, and documented experimental results, limitations, and model-performance trade-offs. |
| Company Bankruptcy Prediction | Classification, financial risk analytics | Developed a machine-learning workflow for bankruptcy prediction, including data preprocessing, class-imbalance handling, model evaluation, and interpretation of financial risk indicators. |
Programming & Analysis
- Python, R, SQL
- pandas, NumPy, scikit-learn, SciPy
- Jupyter Notebook, Quarto / R Markdown
Machine Learning & Statistics
- Regression and classification modeling
- Feature engineering and model validation
- Hypothesis testing and experimental design
- Exploratory data analysis and statistical reporting
Data Visualization & Communication
- Matplotlib, Seaborn, Plotly, ggplot2
- Dashboard and report development
- Technical writing and research presentation
Tools & Workflow
- Git and GitHub
- Reproducible project organization
- Documentation-first development
- Collaborative research workflows
- Applied machine learning for real-world decision support
- Responsible and interpretable AI
- Data-driven social, behavioral, and business insights
- Reproducible research and open analytics practices
I'm interested in opportunities that combine data science, research, and product-minded problem solving, especially roles or collaborations involving machine learning, analytics engineering, applied research, or data storytelling.
- Email: bjdaniel00@gmail.com
- GitHub: Jimin0731
Thanks for visiting my profile! Feel free to explore my repositories and reach out if you'd like to collaborate.