Binal Digital Twin MCP Server

BINAL SHAH Junior Data Analyst | Python, SQL & Data Analytics sbinal182@gmail.com | 0403 892 199 | linkedin.com/in/binalshah | github.com/binal182 Hornsby, NSW 2077 ________________________________________ PROFESSIONAL SUMMARY Recent IT graduate with hands-on experience in Python, SQL, and database design. Built data pipelines, designed relational databases, and created analytics systems through academic and internship projects. Proven leadership through training 6+ team members and coordinating 200+ person events. Seeking Junior Data Analyst role to apply technical skills and grow toward Data Engineering. Key Skills: Python • SQL • Data Analysis • Database Design • Data Pipelines • Excel • Team Training • Project Coordination ________________________________________ TECHNICAL SKILLS Programming Languages: Python, JavaScript/TypeScript, Java, PHP Data & Analytics: Python (Pandas, NumPy), SQL (SQLite, PostgreSQL, MySQL), Excel, Data processing Databases: SQLite, PostgreSQL, MySQL, ChromaDB, Upstash, Database design, Query optimization Web Development: Next.js, React, Flask, Tailwind CSS, shadcn/ui Tools: Git/GitHub, VS Code, GitHub Copilot, Claude Sonnet, Vercel, Deputy Specialized: RAG systems, Vector databases, Computer vision (face_recognition library), AI agent development ________________________________________ PROFESSIONAL EXPERIENCE AI/Data Intern | AusBiz Consulting, Sydney | Jul 2025 - Sep 2025 Developed AI-powered Digital Twin platform using cutting-edge spec-driven development methodology combining GitHub Copilot, Claude Sonnet 4.0, and v0 for an integrated AI-assisted workflow. • Architected and deployed dual-vector database system (ChromaDB for local development + Upstash for production) handling vector embeddings with optimized retrieval performance • Engineered automated data transformation pipeline converting unstructured resume text into 50+ searchable JSON chunks with semantic embeddings for intelligent querying • Built production-grade RAG (Retrieval-Augmented Generation) system enabling natural language queries against professional profile data with context-aware responses • Implemented continuous integration testing framework using custom Food RAG validation system to ensure 95%+ query accuracy • Developed modern web application using Next.js 15 App Router, React 19 Server Components, and Vercel AI SDK for seamless AI integration • Pioneered multi-AI tool development workflow: GitHub Copilot for code generation, Claude Sonnet 4.0 agent mode for architecture decisions, v0 for UI/UX rapid prototyping Technologies: Next.js 15, React 19, Python, ChromaDB, Upstash (Vector DB), Claude Sonnet 4.0, GitHub Copilot, Vercel AI SDK, MCP Protocol, shadcn/ui, Tailwind CSS Impact: Created first-of-its-kind interactive resume technology demonstrating modern AI development practices and production-ready RAG implementation ________________________________________ Team Leader - Customer Experience & Training | Zeus Street Greek, North Willoughby | Dec 2022 - Present Led comprehensive training program and operational excellence initiatives in high-volume food service environment serving 100+ customers daily. • Designed and implemented structured training curriculum for 6+ new hires covering POS systems (point-of-sale), food safety compliance, customer service protocols, and operational workflows • Achieved 40% reduction in onboarding time (from 4 weeks to 2.4 weeks) through systematic training methodology with milestone-based competency tracking • Improved staff retention metrics by creating supportive learning environment with regular performance feedback and skills development focus • Managed digital workforce coordination using Deputy platform for shift scheduling, task assignment, and real-time operational communication across 10+ team members • Maintained consistent high-volume service delivery handling 20+ customer interactions per shift while coaching junior staff during peak periods • Resolved customer escalations with 95%+ satisfaction rate through active listening, problem-solving, and service recovery techniques • Recognized by management for exceptional teamwork, reliability during closing procedures, and maintaining quality standards under pressure Technologies: Deputy (digital task management), POS systems, Microsoft 365 Key Achievement: Transformed training process from ad-hoc approach to systematic, measurable program with documented procedures and performance metrics ________________________________________ Local Coordinator | Students for Liberty Australia, Sydney | Jan 2023 - May 2024 Managed large-scale educational programs and volunteer operations across Sydney and Melbourne, coordinating with international leadership team. • Orchestrated logistics for 200+ participant workshops across 5+ universities (USYD, UNSW, UTS, Macquarie, Western Sydney) including venue coordination, speaker management, and technology setup • Built and managed 13-member volunteer team across Sydney and Melbourne markets using regular team meetings, goal-setting frameworks, and performance recognition programs • Achieved 85% engagement success rate measured through attendance tracking, participant feedback surveys, and program conversion to ongoing membership • Managed hybrid event technology infrastructure seamlessly integrating Microsoft Teams, Zoom, and in-person components for accessible program delivery • Coordinated budget approval and expense tracking for multiple concurrent programs, ensuring financial accountability and ROI documentation for leadership reporting • Maintained consistent volunteer engagement through weekly Google Meet check-ins, social meetups, and professional development opportunities Technologies: Microsoft Teams, Zoom, Google Meet, Project management tools, Hybrid event technology Impact: Successfully scaled educational programs across two major metropolitan areas while maintaining high engagement and volunteer retention rates ________________________________________ KEY PROJECTS My Digital Twin - AI-Powered Professional Platform Lead Developer and AI Integration Specialist | Jul 2025 - Sep 2025 Production-quality AI platform demonstrating modern RAG architecture, vector database optimization, and AI-assisted development workflows. • Engineered sophisticated data transformation pipeline processing structured resume data into 50+ semantic chunks with metadata tagging, enabling granular and context-aware information retrieval • Implemented dual-vector database architecture: ChromaDB for local development iteration + Upstash serverless vector DB for production deployment with automatic scaling • Built RAG (Retrieval-Augmented Generation) system using vector similarity search with cosine similarity matching, enabling natural language queries like "What are Binal's AI projects?" with contextually accurate responses • Developed automated quality assurance framework using custom Food RAG testing system to validate retrieval accuracy, response coherence, and system performance across 20+ test query scenarios • Created modern full-stack application leveraging Next.js 15 App Router architecture, React 19 Server Components for optimal performance, and Vercel AI SDK for streaming AI responses • Pioneered integrated AI development workflow: Utilized GitHub Copilot for 60%+ code generation, Claude Sonnet 4.0 agent mode for architectural decisions and debugging, and v0 for rapid UI prototyping - demonstrating modern AI-assisted software engineering • Implemented Model Context Protocol (MCP) for advanced AI agent integration and context management across development tools Technologies: Next.js 15, React 19, Python, ChromaDB, Upstash, Vector Embeddings, Vercel AI SDK, Claude Sonnet 4.0, GitHub Copilot, v0, MCP Protocol, shadcn/ui, Tailwind CSS Technical Innovation: First implementation combining local + serverless vector databases for development-production parity in RAG applications GitHub: github.com/binal182/binal_digital-twin_py ________________________________________ Smart Attendance System - Computer Vision Capstone Full-Stack Developer and System Architect | Academic Capstone Project Comprehensive database-driven attendance analytics platform with computer vision integration, built entirely independently from system design to deployment. • Architected normalized relational database schema (SQLite) with 5+ interconnected tables (Users, Classes, Subjects, Attendance, Timetables) following Third Normal Form (3NF) principles for data integrity and query optimization • Designed and implemented three-tier role-based access control system with completely differentiated user experiences: • Admin Portal: System-wide user management, comprehensive attendance analytics across all classes, bulk operations, and data export capabilities • Teacher Portal: Subject-specific attendance tracking, class roster management, trend analysis dashboards, and CSV report generation for institutional reporting • Student Portal: Personal attendance tracking with percentage calculations, subject enrollment views, teacher contact information, and integrated timetable with real-time schedule display • Integrated computer vision pipeline using face_recognition library with 128-dimensional facial encoding for automated attendance capture, reducing manual entry time by 90% and eliminating human error • Implemented Flask-SQLAlchemy ORM for database abstraction enabling easy migration to PostgreSQL/MySQL for production scalability while maintaining code portability • Built secure authentication system with Werkzeug password hashing (PBKDF2 with salt) and Flask-CORS for cross-origin security in web deployment scenarios • Created automated reporting engine generating downloadable CSV reports with Pandas for data export, enabling integration with institutional systems and further analysis • Developed complex SQL query architecture utilizing JOINs across multiple tables, aggregation functions for attendance percentages, and date-based filtering for historical trend analysis • Engineered complete image processing pipeline using NumPy for numerical face encoding operations and Pillow for image manipulation, all processed locally for privacy compliance Technologies: Python 3.8+, Flask, SQLite (SQLAlchemy ORM), face_recognition library, NumPy, Pillow, Pandas, Werkzeug, Flask-CORS, HTML/CSS Database Design Highlights: • Multi-table relational architecture with foreign key relationships and referential integrity • Indexed columns for optimized query performance on frequently accessed data • Normalized schema preventing data redundancy and update anomalies Technical Achievement: Independently built production-ready system demonstrating full-stack development, database architecture, security implementation, and computer vision integration without external assistance Scale: System designed to handle 1000+ users, 50+ classes, and 10,000+ attendance records with efficient query performance ________________________________________ EDUCATION Bachelor of Information Technology | Victoria University, Sydney | Graduated September 2025 Relevant Coursework: • Web & Mobile Development • Cloud Application Development • Data Analytics for Cyber Security • Big Data • ICT Business Analytics • Cyber Security Essentials (TCP/IP, DNS, DHCP) ________________________________________ LEADERSHIP & ACHIEVEMENTS • Trained and mentored 6+ new hires with measurable improvement in retention • Reduced onboarding time by 40% through systematic training approach • Coordinated 13-member volunteer teams across Sydney and Melbourne • Led event planning for 200+ student participants • Created first-of-its-kind interactive resume technology using vector embeddings • Recognized by Zeus Street Greek leadership for consistently high customer satisfaction and teamwork ________________________________________ ADDITIONAL INFORMATION Visa Status: Student Visa (Subclass 500) - Expires November 28, 2025. Applying for 485 Graduate Visa in November 2025 (2-4 years full work rights upon approval). Availability: Part-time during study, full-time post-graduation. Available for rotating rosters including evening shifts. Transport: Valid NSW driver's license. Reliable public transport user. Relocation: Open to relocating from Sydney for the right opportunity. Salary Expectation: $65,000 - $70,000 per annum ________________________________________ REFERENCES Callum Bir AusBiz Consulting Supervisor - AI/Data Internship (Jul-Sep 2025) Available upon request Sailesh Upreti Zeus Street Greek Manager - Customer Experience & Training (Dec 2022-Present) Phone: 0452 389 096