Shane Fitzpatrick
Data Science Portfolio
About Me
I'm an Economics student at Binghamton University minoring in Digital and Data Studies. My academic journey combines economic theory with modern data science techniques, allowing me to analyze complex market dynamics and derive meaningful insights from data.
I've developed a strong foundation in both quantitative analysis and programming, with particular interests in applying machine learning and statistical modeling to solve real-world economic problems, focusing on market analysis and predictive analytics.
Relevant Coursework
- Economic Analysis with Python
- Statistical Analysis with R
- Database Fundamentals with SQL
- Data Visualization with Python
- Intro to Coding
Technical Skills
Programming & Data Analysis
Python (Pandas, NumPy, Matplotlib, Scikit-Learn), SQL, R, Tableau
Geospatial & Visualization
ArcGIS, Geopandas, Folium, Matplotlib, Seaborn
Machine Learning & Statistics
Linear Regression, OLS Regression, Random Forest, ANOVA
Data Management & APIs
FRED API, Zillow Data, Web Scraping
Tools & Technologies
Google Suite, Excel (VLOOKUP, PivotTables), PC Assembly & Diagnostics
Featured Projects
Investor Forecasting Simulation
Designed an algorithmic investment simulation model that analyzes historical market data to generate forecasting scenarios. Features multi-portfolio strategy comparison, risk evaluation metrics, and visualization of projected returns across diverse market conditions.
Used Car Market Analysis
Statistical exploration of used car market data examining key factors affecting vehicle valuation. Analyzes relationships between vehicle specifications (cylinders, horsepower, torque) and market pricing through regression modeling and feature importance visualization.
Bikeshare NYC Analysis
Comprehensive analysis of NYC's Citi Bike program using geospatial and temporal data. Features time series analysis of usage patterns, station flow mapping, weekly trend analysis with rolling averages, and peak usage identification to optimize system operations.
Data Visualizations
Multi-Portfolio Investment Strategy Comparison
Comparative analysis of investment strategies against benchmark performance over time.
Bikeshare Ridership with 7-Day Rolling Average
Weekly trend analysis of Citi Bike usage with smoothed data to identify seasonal patterns.
Horsepower Distribution by Cylinder Configuration
Average horsepower analysis for different engine cylinder counts in the used car market.
Horsepower vs. Torque Correlation
Scatter plot showing the positive relationship between vehicle horsepower and torque measurements.
Bikeshare Station Net Flow Map
Color-coded visualization of station outflow volumes to identify optimal locations for bike rebalancing and station placement.
Hourly Bikeshare Usage Pattern
Daily ridership distribution showing peak usage during morning and evening commute hours.
Get in Touch
Interested in discussing economics, data science, or potential opportunities? Let's connect!