1) UI/UX Design: Drove the user-friendly UI/UX redesign by conducting internal user interviews to identify key pain points and desired gains, which informed the creation of user persona, user journey mapping, empathy map, prioritization matrix and ultimately led to a high-fidelity clickable Figma prototype that optimized user experience. 2) Data Science Analysis: Conducted clustering analysis across the full data science lifecycle, utilizing a multi-algorithm approach (K-Means, DBSCAN, Mean Shift, Spectral) on two multi-feature datasets from 500+ cities in Python (Pandas, NumPy, Scikit-learn, SciPy, Plotly, Matplotlib, Seaborn) via Jupyter Notebook, which identified the optimal clustering models and most robust city clusters. 3) Insight Communication: Translated the complex cluster analysis results into insights by creating QGIS visualizations that I presented to the mentor, team, and managers, leading to a clearer understanding of regional disparities and opportunities. 4) Knowledge Sharing: Authored and distributed a comprehensive step-by-step QGIS tutorial to the team for data visualization based on my workflow, standardizing the team’s approach to spatial data.