Open to internship and job opportunities

Hi, I'm Jacob Ball

Marine Corps veteran pursuing an accelerated M.S. in Cybersecurity at Fordham University, with a concentration in artificial intelligence. Focused on building expertise in security fundamentals alongside emerging AI applications for threat detection and analysis, supporting a career path in cybersecurity and AI-driven security analytics. Proficient in Python, SQL, and C++, with hands-on military experience designing and maintaining mission-critical network infrastructure for 200+ users, a foundation that directly informs my cybersecurity focus. Actively seeking internship and full-time opportunities in cybersecurity and AI-driven security analytics.

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Career

Work Experience

Evaluated and annotated multimodal AI outputs across text, image, audio, and video formats, maintaining strict quality benchmarks within a human-in-the-loop workflow.
Analyzed AI failure cases, applied image transformations, and annotated objects in images and videos using coordinates and timestamps to improve model accuracy and consistency.
Developed structured multimodal instructions for video style transfer tasks and provided feedback to support continuous AI learning and optimization.

Ensured safety and security of premises, enhancing operational efficiency by implementing new patrol logging procedures.
Addressed member concerns with professionalism, demonstrating problem-solving and time management skills.
Oversaw nightly closure procedures for the club, ensuring the safe departure of all members and staff before executing comprehensive lockdown protocols.

Secured and administered classified LAN/WAN infrastructure for 100+ users, enforcing access controls, security protocols, and network hardening procedures to maintain 99.999% uptime during mission-critical operations.
As Platoon Network Chief, led secure network deployment for the Balikatan 2023 joint military exercise, establishing and hardening communications infrastructure supporting 200+ coalition personnel in a high-stakes operational environment.
Automated routine security configurations and network administrative tasks using scripted solutions, reducing configuration time by 30% while minimizing human error and attack surface.

Academic

Education

My academic background and professional certifications.

Degrees

M.S. Data Science

Fordham University

2027 · New York, NY

Relevant Coursework

Algorithms for Data Science

B.S. Information Technology & Systems

Fordham University

2026 · New York, NY

3.85

GPA

Dean's List 2024–2025Magna Cum Laude

Relevant Coursework

Computer Science I & IIData StructuresDatabase SystemsWeb ProgrammingSecure Cyber NetworksData Comm & Networks

Certifications

Python Basics for Data Science

IBM · 2023

Expertise

Technical Skills

Technologies and tools I work with professionally.

Programming Languages

Python100%

SQL90%

C++75%

JavaScript50%

HTML50%

Data Science & ML

pandas90%

scikit-learn80%

NumPy80%

Feature Engineering65%

Time Series Analysis65%

yfinance API65%

Cybersecurity

Network Security85%

Access Control & IAM80%

Security Hardening80%

Threat Detection & Analysis70%

Vulnerability Assessment65%

Incident Response65%

Networking & Infrastructure

LAN/WAN Design85%

TCP/IP85%

Network Architecture80%

Data Communications80%

Linux75%

Frontend

HTML/CSS70%

Bootstrap70%

Backend & Databases

MySQL90%

Node.js60%

Tools

Jupyter Notebook100%

Git95%

VS Code100%

Wireshark75%

Nmap70%

Kali Linux65%

Agile60%

Portfolio

Featured Projects

A selection of projects that demonstrate my technical capabilities.

Stock Market Data Pipeline & Prediction Model

End-to-end machine learning pipeline for predicting S&P 500 stock movements using historical market data.

Built a full data ingestion pipeline to collect, normalize, and clean historical market data using the yfinance API
Developed a Random Forest classifier with a backtesting engine achieving 55.7% precision across 9,000+ historical trading days
Implemented train-test splits and data leakage prevention for reliable model evaluation

Pythonscikit-learnpandasyfinance APITime Series Analysis

Source

Directed Weighted Graph with BFS

A C++ implementation of a directed weighted graph abstract data type with full traversal capabilities.

Implemented adjacency matrix representation using dynamic 2D arrays with full vertex and edge operation support
Developed a breadth-first traversal algorithm achieving O(V+E) time complexity across 7+ vertices and 9+ weighted edges
Utilized STL queue and vertex marking system for efficient graph exploration

C++Graph TheorySTLDynamic Memory Management

Dynamic Sinusoidal Graphing Tool

A C++ program that dynamically calculates and renders sinusoidal functions based on user-defined input.

Designed dynamic sinusoidal function calculations with optimized iterative performance based on user input
Applied modular programming techniques to improve code maintainability, reducing debugging time by 20%
Produced clean graphical outputs directly from algorithmic computation

C++Algorithm DesignGraphical Outputs

Want to see more?

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Contact

Get In Touch

Think I'd be a good fit for a role or have a project in mind? I'd enjoy hearing from you.

Contact Information

jeball22@gmail.com

203-321-7755

Greenwich, CT, USA

Social Profiles

LinkedIn GitHub