Data Science Portfolio – Stephanie Smith

Welcome! This repository serves as an index of my selected data science and analytics projects.

A more detailed write up of each project along with my resume can be found on my personal website: https://www.notion.so/welcome-to-my-data-science-portfolio-2075d2b3ab7880fea009eaf700408b20

📊 Featured Projects

🎧 Spotify User Segmentation & Behavioral Analysis

Goal: Identify distinct Spotify user segments based on demographics, listening behavior, and subscription preferences.
Methods: KModes clustering (categorical data), silhouette & elbow methods, association rule mining (support, confidence, lift).
Tools: Python, pandas, kmodes, mlxtend, matplotlib, seaborn.
🔗 Repository: https://github.com/stjsmith8/user-segmentation

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💳 Credit Card Customer Churn Prediction

Goal: Predict customer churn and identify behavioral drivers of attrition to support proactive retention strategies.
Methods: Logistic Regression, Random Forest, XGBoost, SMOTE, feature importance, ROC/AUC analysis.
Tools: Python, scikit-learn, XGBoost, pandas, matplotlib, seaborn.
🔗 Repository: https://github.com/stjsmith8/customer-churn-prediction

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🧠 Core Skills

• Python, R, SQL, SAS
• Statistical Modeling & Machine Learning
• Time Series Forecasting
• Clustering & Segmentation
• Data Visualization (Tableau, ggplot2)
• Program Evaluation & Applied Research

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📬 Contact

• LinkedIn: https://linkedin.com/in/YOURNAME
• GitHub: https://github.com/USERNAME