Muhammad Ismail Hafeez

About Me

I am a final-year Data Science student at the National University of Computer and Emerging Sciences (NUCES), Islamabad. My experience spans data analysis, machine learning, and data engineering, with a strong focus on building scalable and intelligent data-driven solutions.

Work Experience:

1. Data Intern — Dakota (Oct 2025 – Jan 2026) - Helped Dakota enrich their data in Dakota Marketplace by collecting private companies data in the US market. Utilized Google Sheet to maintain records
2. AI Intern — Automotive Artificial Intelligence (AAI-GmbH) (June 2025 – July 2025) - Developed an AI-powered chatbot for ISO standard queries using LangChain and Vertex AI. The system utilized vector embeddings for semantic search via Gemini 2.5 Flash, covering the complete development lifecycle, from data processing to backend integration and frontend deployment.
3. Lab Demonstrator — NUCES (2024 – 2025) - Assisted junior students in understanding programming fundamentals and object-oriented programming (OOP) concepts in C++. Responsibilities included resolving queries and grading lab assignments.

Previous projects:

1. UpClout (September 2025 ~) - Final Year Project focused on social media (Instagram) analytics. It connects brands and content creators through AI-driven recommendations and performance insights.
2. Near-Real-Time Data Warehouse (Nov 2025) - Designed a hybrid-join stream-based join algorithm for processing Walmart sales transactions. Automated ETL pipeline, enabling real-time data integration from CSV sources. Developed 20 OLAP analytical queries to support business intelligence and analytics.
3. ISO Compliance Chatbot (June 2025 - July 2025) - Developed a GCP-deployed chatbot using Docker containers for efficient scaling and maintenance.
4. TB Dashboard (November 2024) - This dashboard visualizes insights into Tuberculosis (TB) cases across the globe, utilizing data from the World Health Organization (WHO) TB Reports. Built using D3.js, JavaScript and HTML.
5. Music Recommendation System (May 2024) - Created a real-time recommendation platform using Apache Spark, Kafka, and Python, deployed with Flask and backed by MongoDB.

Technical Skills

• Programming & Tools: Python, SQL, C++, Docker, Flask
• Data & AI Frameworks: Pandas, NumPy, Scikit-learn, LangChain, Vertex AI
• Big Data Technologies: Apache Kafka, Apache Spark, Dask
• Visualization: D3.js, Power BI, Matplotlib
• Databases: MongoDB, PostgreSQL, MySQL

I enjoy tackling data challenges and writing clean, reusable, and efficient code. As a fast learner passionate about AI and data engineering, I’m always eager to contribute to impactful projects.