🔨 Background: Son of a steelworker turned computer programmer
📊 Passion: Political data analysis and electoral trends
💻 Focus: Building tools for real-world political analysis
🎯 Current Project: Targeting 2026 House battlegrounds with data-driven tools

I'm an African American computer programmer with working-class roots and a passion for political data. Coming from a steelworker family in Harleyville, SC - a small town in the Lowcountry just north of Colleton County (an Obama-Trump county similar to Luzerne County, PA) - whose parents lived through the Civil Rights era, I bring an authentic perspective to analyzing electoral trends, particularly in working-class districts that have experienced significant political realignment.

Like my father who built with steel, I've inherited the drive to build - just with code instead of metal. My interest in politics emerged early, inspired by my late uncle who served as the only Democrat on our county council until he passed in 2018. The county honored his legacy by naming Davis-Bailey Park after him, located next to the courthouse - a daily reminder of public service and political engagement that shaped my perspective.

Interestingly, my name Shamar means "to guard" in Arabic - perhaps fitting for someone dedicated to guarding democratic processes through data analysis and electoral integrity, continuing the work my parents' generation fought to secure.

As a neurodiverse individual with level 1 autism, I naturally approach problems from unique angles and excel at pattern recognition - skills that prove invaluable in electoral data analysis and seeing trends others might miss.

Currently studying CPT-236 Computer Programming and applying those skills to real-world political analysis challenges.

A Java application for analyzing electoral competitiveness - built after dissecting 2020-2024 presidential realignment patterns. This tool serves as the foundation for targeting the 25-30 battleground House seats that will determine control in 2026.

Key Features:

• 🗳️ Electoral margin calculation and race rating system
• 📈 Validated against actual 2024 election outcomes
• 🎯 Strategic focus on competitive battleground districts
• 📊 Professional political analysis methodology

Tech Stack: Java, Political Analysis, Electoral Data
Background: Working-class perspective meets programming skills

The MarginCalculator methodology has been validated against actual election outcomes:

• Pennsylvania U.S. Senate (2024): Correctly classified as "Tossup" - went to legal challenges
• Congressional Districts: Accurately predicted competitive races in PA-08, CA-45
• Electoral Trends: Captures Obama-Trump district realignment patterns

🔗 View MarginCalculator Project

After analyzing presidential electoral trends from 2020-2024, I'm building systematic tools for targeting battleground House seats in the 2026 midterms. Rather than attempting to predict all 435 races, the focus is on the 25-30 truly competitive districts that will determine House control.

Entrepreneurial Opportunity: This foundation could scale into a comprehensive political data platform, serving campaigns, media outlets, and research institutions with authentic, working-class perspective on electoral analysis.

Background: This project emerged from living near Colleton County, SC - an Obama-Trump county that mirrors the famous Luzerne County, PA realignment patterns. The MarginCalculator methodology captures working-class political shifts across regions.

📝 Coming Soon: "From Steel to Code: Obama-Trump Counties Explained"
📊 Coming Soon: "From Steel to Code: How MarginCalculator Captures Realignment"
🗳️ Coming Soon: "From Steel to Code: 2026 House Battlegrounds"

• Economic Anxiety Patterns: Manufacturing decline → political messaging vulnerability
• Demographic Transitions: Population shifts → electoral realignment
• Cultural Change Responses: Traditional communities → new political coalitions
• Predictive Accuracy: Algorithm validated against 2024 outcomes
• Obama-Trump Tracking: 20-year analysis of Luzerne County, PA and Colleton County, SC realignment patterns

2024 MarginCalculator Validation:

• Luzerne County, PA: Trump +19.1% → "Safe Republican"
• Colleton County, SC: Trump +18.2% → "Safe Republican"
• Cross-Regional Convergence: Both counties reached similar endpoints despite different starting positions

🔗 Follow on Medium for detailed analysis

Programming: Java, Data Analysis, Algorithm Design
Political Analysis: Electoral trends, Battleground identification, Working-class voting patterns
Academic: CPT-236 Computer Programming, Professional software development practices

• 🔗 GitHub: @Tenjin25
• 📧 Contact: Available for political tech opportunities and data collaboration
• 🎯 Career Fair: September 4, 2025 - Looking forward to showcasing electoral analysis tools!

Building the future of political analysis, one algorithm at a time 🚀

"Do you see the code yet?" 👁️‍🗨️