Education
Gettysburg College — Gettysburg, PA
B.S. in Computer Science, Minor in Mathematics, Data Science — GPA: 3.75/4.0
Expected May 2027
Technical skills
Languages: Python, Swift, Java, PowerShell
Technologies: SwiftUI, Firebase, Cloud Firestore, REST APIs, Git, GitHub, Azure
Libraries: NetworkX, Pandas, NumPy, SciPy, Matplotlib, pytest
Professional experience
Sullivan & Cromwell LLP — New York, New York
June 2026 – Present
Electronic Discovery & Litigation Support Intern
- Developed PowerShell-based workflow automation solutions within AgilityBlue to streamline data disposition processes, reducing manual coordination across legal, technology, and information security teams.
- Integrated AgilityBlue REST APIs to automate project lifecycle tasks and eliminate bottlenecks within electronic discovery workflows.
- Researched and evaluated emerging technologies, including Azure services, AI-assisted review platforms, and modern communication tools, contributing findings to quarterly firm-wide technology briefings.
- Evaluated and improved data management workflows across the electronic discovery lifecycle with litigation support professionals.
Projects
DOBLE – iOS Emergency Medical Services Application
Jun 2025 – September 2025
Lead Developer, Darien EMS – Post 53
- Swift
- SwiftUI
- Firebase Authentication
- Cloud Firestore
- Led design, development, and deployment of a full-stack iOS platform used by 130+ EMS personnel, centralizing scheduling, attendance, training resources, communications, and organizational records.
- Designed and implemented the application architecture using Swift, SwiftUI, Firebase Authentication, and Cloud Firestore, enabling secure access control and real-time data synchronization.
- Deployed the application through Apple's private distribution program and achieved 92% organizational adoption, replacing multiple third-party services while significantly reducing software costs.
YouTube Recommendation Network Analysis
- Python
- NetworkX
- Pandas
- NumPy
- SciPy
- Matplotlib
- pytest
- Built an end-to-end Python analytics pipeline to analyze 7,079 YouTube channels and 401,384 recommendation relationships, constructing a weighted network for large-scale ideological drift analysis.
- Developed reproducible Monte Carlo-style weighted random walk simulations to model recommendation behavior and measure changes in ideological direction, extremity, assortativity, and clustering.
- Developed a test-driven Python codebase with 72 automated tests, reproducible simulation results, and clear documentation to support reliable experimentation and analysis.
Leadership & awards
Secretary, ACM, Gettysburg College
Jan 2025 – Jan 2026
Vice President, Darien EMS – Post 53 — Town of Darien Exemplary Leadership Award
Sophomore Inductee, Pi Mu Epsilon Mathematical Honor Society