Welcome to my GitHub Pages portfolio! I'm Harshul Shah, a Master’s student in Statistics (Data Science) at the University of Texas at Dallas, with a passion for using data-driven insights to solve real-world problems — especially in the world of sports analytics, machine learning, and cloud-based automation.
- 📍 Based in Plano, Texas
- 🎓 Master’s in Statistics (Data Science), UT Dallas (2025)
- ⚽️ First Team Analysis Intern at FC Dallas
- 🛠 Experienced in building ML tools, automating data pipelines, and delivering performance analysis in both sports and business domains
- Tech Stack: Python, scikit-learn, Pandas, Random Forest, K-Means Clustering
- Overview: A machine learning-based tool to predict player promotion eligibility based on physical and GPS-based performance data from academy players.
- Impact: Achieved ~92% accuracy in classifying promotion potential using real-world match data.
- Tech Stack: Python, Pandas, Plotly, Web Scraping
- Overview: A weekly-updating tool for recommending optimal FPL swaps, captain picks, and chip usage based on player stats and fixture difficulty.
- Tech Stack: Python, Random Forest, Streamlit, Data Preprocessing
- Overview: Crop recommendation engine based on NPK soil values, designed for agricultural enhancement in developing regions.
- Tech Stack: Python, OpenCV, Tesseract OCR
- Overview: Real-time vehicle and number plate recognition system using computer vision, with potential smart parking/alert integrations.
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🎯 FC Dallas – First Team Analysis Intern
Created GPS-based tracking models, prepped match reports, and supported live training analysis. -
🧠 Gameplay Inc – Data Engineering Intern
Built Python scripts using Google Places API to automate identification of sports fields across the USA. -
🏢 EY India – Technology Consultant Intern
Worked on SAP data migration pipelines for enterprise-level clients. -
🏨 MakeMyTrip India – Marketing Analyst Intern
Developed Python dashboards for campaign effectiveness. -
🔐 Cy5.io – Security Analyst Intern
Analyzed malware detections using regex-based anomaly pattern recognition.
- Languages: Python, SQL, SAS, R, Bash
- Libraries/Tools: scikit-learn, Pandas, NumPy, Matplotlib, Streamlit, OpenCV
- Cloud/Infra: AWS S3, EC2, Google API, Git
- Domains: Sports Analytics, Data Engineering, ML Modeling, Computer Vision
Thanks for stopping by! Feel free to explore my projects, suggest collaborations, or just say hi.### 🚀 Explore the Repositories
Click through the repositories to explore my code, case studies, and contributions to real-world applications in data science, sports analytics, and automation.
Thank you for visiting!