This repository hosts my personal portfolio website, built with HTML and CSS and deployed using GitHub Pages.
🌐 Visit the live portfolio: https://joannar77.github.io
I am a Data Scientist with a Master of Science in Data Science and a background in Information Technology Management, Accounting, Finance, and Business Analytics.
I specialize in transforming complex datasets into actionable insights through data engineering, statistical modeling, machine learning, predictive analytics, and business intelligence. My projects span the complete analytics lifecycle—from data collection and preparation to model development, deployment, and interactive visualization.
- Python
- SQL
- Pandas
- NumPy
- Scikit-learn
- Statsmodels
- FastAPI
- Docker
- MongoDB
- PostgreSQL
- Tableau
- Selenium
- Git & GitHub
Repository: https://github.com/joannar77/nevada-appellate-timing-study
A statewide judicial analytics study examining more than 5,700 Nevada appellate cases using Selenium, feature engineering, predictive analytics, and multiple linear regression to identify factors associated with appellate disposition timing.
Technologies: Python • Selenium • Pandas • Statsmodels • Scikit-learn
🎥 Project Walkthrough
Repository: https://github.com/joannar77/flight-delay-ml-pipeline
Developed an end-to-end machine learning workflow for predicting flight delays, including data engineering, feature engineering, model training, experiment tracking, and evaluation.
🎥 Project Walkthrough
Repository: https://github.com/joannar77/flight-delay-api-deployment
Deployed a trained machine learning model as a production-style REST API using FastAPI, Docker, and automated testing to demonstrate production-ready model serving.
🎥 Project Walkthrough
Repository: https://github.com/joannar77/churn-prediction-random-forest
Developed a Random Forest classification model to identify customers at risk of churn using demographic, billing, and service usage data.
🎥 Project Walkthrough
Repository: https://github.com/joannar77/customer-segmentation-kmeans
Applied unsupervised machine learning to identify meaningful customer segments that support targeted marketing, customer engagement, and retention strategies.
🎥 Project Walkthrough
Repository: https://github.com/joannar77/healthfit-mongodb-project
Designed optimized MongoDB aggregation pipelines that generate actionable healthcare and business insights using both Python and JavaScript implementations.
🎥 Project Walkthrough
- Housing Price Prediction using Multiple Linear Regression
- Luxury Home Classification using Logistic Regression
- Housing Price Prediction using Principal Component Analysis (PCA)
- Telecommunications Revenue Forecasting using ARIMA Time Series Analysis
- Customer Churn Dashboard (Tableau)
- Computer Vision Image Classification
- Sentiment Analysis using LSTM Neural Networks
- Employee Turnover Data Cleaning (WGU Excellence Award)
- Business Performance Analysis
- U.S. Census Data Analysis
- Supply Chain Optimization using Mixed Integer Linear Programming (MILP)
Most repositories include short video walkthroughs demonstrating the project methodology, implementation, and business interpretation.
Across my portfolio you will find projects involving:
- Data Engineering
- Data Cleaning & Validation
- Web Scraping with Selenium
- Statistical Modeling
- Predictive Analytics
- Machine Learning
- Deep Learning
- Time Series Forecasting
- REST API Development
- Docker Deployment
- MongoDB Aggregation Pipelines
- Tableau Dashboards
- Business Intelligence
- Optimization Modeling
- Public Sector Analytics
- Python
- SQL
- JavaScript
- HTML
- CSS
- Pandas
- NumPy
- Scikit-learn
- Statsmodels
- TensorFlow / Keras
- Matplotlib
- Seaborn
- FastAPI
- PostgreSQL
- MongoDB
- Tableau
- Docker
- Git
- GitHub
- Selenium
- Jupyter Notebook
Master of Science in Data Science
Western Governors University
Bachelor of Science in Information Technology Management
Western Governors University
Built with HTML, CSS, and GitHub Pages.
Last updated: June 2026.