Daood Khan

I’m a Computer Science graduate specializing in fast, scalable, and responsive web applications, shaped by both frontend delivery and data analysis training at Capgemini.

In my frontend internship at D2I Technology, I built and deployed production-ready web tools used by thousands of active users. I improved user experience by reducing page load times by 40% through UI refactoring and code-splitting, and I supported cross-device link sharing with a browser detection system.

I also focused on measurable growth and utility, boosting user growth by 60% with a social media content generator and building daily-use features like finance calculators and developer utilities. I approach code through the lens of user-impact and performance metrics, aiming for reliable, high-performing interfaces.

On the data side, I completed structured Data Analyst training covering data cleaning pipelines, predictive profiling structures, and analytics for decision-making. I back this with projects like a real-time MERN mental health platform using WebSockets and a peak electricity demand forecasting system built with Python, Scikit-learn, XGBoost, and FastAPI—always with an emphasis on reliability, privacy, and actionable insights.