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TJLSmith0831/README.md

Header

A Full-Stack Engineer & Data Scientist crafting scalable, elegant solutions that bridge intuitive UX with powerful backend systems. Passionate about turning complex problems into clean, efficient code.


  • 🔭 I currently work at PILYTIX, where I lead full-stack development and data science initiatives to power predictive models and CDP-driven marketing solutions for major sports teams, university foundations, and live entertainment venues. My work spans secure, scalable infrastructure, custom lead scoring algorithms, and AI-powered engagement tools

  • 🌱 Always learning — pursuing MongoDB Associate Developer (Python) and AWS Cloud Practitioner certifications

  • 📜 Certified in Docker Foundations, Tableau Desktop Specialist, Microsoft Excel Expert, Julia & R Programming, Big Data SQL, TypeScript, React, and JavaScript

  • 💬 Ask me about React, TypeScript, Python, or building full-stack systems from scratch

  • 🧠 On the side: I write about tech, build weird MVPs, and chase predictive modeling in sports analytics


💻 Code Contributions


Full-Year Calendar Isometric

🌍 OSS Contributions

View my ongoing Open Source Contributions

🛠️ Languages and Tools



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  1. tenet-app tenet-app Public

    A mobile-first social opinion platform for structured, intentional discourse

    TypeScript

  2. praetor-ai praetor-ai Public

    PraetorAI is an AI-first project management and productivity platform designed to help users break down complex projects into manageable tasks

    JavaScript

  3. ParaLlama ParaLlama Public

    ParaLlama is a TypeScript framework for client-side parallel processing using Web Workers and RxJS Observables. It enables efficient execution of complex tasks, leveraging MessagePack for data seri…

    TypeScript

  4. NBASalaryValuation NBASalaryValuation Public

    Jupyter Notebook

  5. PredictionsNBA2021OpeningWeek PredictionsNBA2021OpeningWeek Public

    This repository holds the programs and files for the predictions on the 2021 NBA Opening Week games. These predictions were made using Random Forest and Decision Tree models.

    Jupyter Notebook

  6. NBA2020Prediction NBA2020Prediction Public

    Using Machine Learning to predict the 2020 NBA Champions

    HTML