Evan Musick
Computer Science Student & Freelance Web Developer
📧 evanmusick.dev@gmail.com 🌐 evanmusick.dev 📍 Springfield, MO 💼 github.com/musickevan1 🔗 linkedin.com/in/evan-musick-49ba15187
Professional Summary

Computer Science and Data Science student at Missouri State University with hands-on experience in full-stack web development and machine learning. Completed 4 freelance websites and multiple ML research projects. Passionate about building scalable applications, automation solutions, and sharing insights through technical content creation.

Education
Bachelor of Science - Computer Science & Data Science
Missouri State University
Fall 2023 - Dec 2026
Dual degree program focusing on software engineering, machine learning, and data analytics. Relevant coursework: Deep Learning, Algorithms & Data Structures, Database Systems, Calculus II, Multivariate Calculus, Computer Networks, Internet Programming. Active participant in "Code Everyday" challenge with 100+ days of consistent GitHub activity.
Professional Experience
Freelance Web Developer
Self-Employed
2023 - Present
  • Completed 4 freelance websites including XZACKT Real Estate, Hoffmangruppe Promotions, and Timber & Threads Retreat
  • Built full-stack applications using React, Next.js, Tailwind CSS, and Supabase with live deployment on Vercel
  • Developed CRM and lead generation tools integrated with Slack & Notion for client management
  • Automated outreach and newsletter workflows using AI tools (OpenRouter, Claude) and n8n
  • Implemented responsive designs with modern web practices and performance optimization
Technical Content Creator
Brain Bytes Newsletter
June 2025 - Present
  • Weekly newsletter focused on AI trends, small models, tools, automation, and reasoning
  • Published consistently on Medium and LinkedIn with growing engagement (1.5K-3K impressions per post)
  • Developed insightful but conversational content with bold visual assets
  • Focus on staying ahead of AI trends in a human-centered way
Machine Learning Researcher
Independent Projects
2024 - Present
  • Built "SteelNet" CNN model and HOG+SVM classifier for steel defect detection on NEU-DET dataset
  • HOG+SVM achieved superior performance with 92.44% accuracy and 92.31% F1 score (CSC 537 final project)
  • Developed TaskML with ML-powered task prioritization and Chartonomics data visualization dashboard
  • Earned top final project score in CSC 537 Deep Learning course for comparative analysis
Key Projects
XZACKT Real Estate Platform
Next.js 14 • Supabase • Tailwind CSS • TypeScript
Full-featured real estate platform with MLS-style property listings, intelligent lead routing, and automated email campaigns. Features responsive design, advanced search functionality, and admin dashboard for property management.
Steel Defect Detection System
PyTorch Lightning • OpenCV • Computer Vision • Machine Learning
Comparative study of CNN vs traditional HOG+SVM approaches for industrial steel surface defect detection. Achieved superior accuracy with deep learning methods on NEU-DET dataset.
Personal CRM (CRMusick)
Next.js • Supabase • Automation • Lead Management
Custom CRM solution with automated lead generation, contact management, and email integration. Features dashboard analytics, task automation, and customer journey tracking.
Technical Skills
Frontend Development
React, Next.js, TypeScript, JavaScript, Tailwind CSS, HTML5, CSS3
Backend & Database
Node.js, PostgreSQL, Supabase, RESTful APIs, SQL, Database Design
Machine Learning & Data
Python, PyTorch, OpenCV, Pandas, NumPy, Computer Vision, Data Analysis
Tools & DevOps
Git, GitHub Actions, Vercel, Docker, Linux, VS Code, Figma
Achievements & Certifications