Ahmed Mustafa Malik

- Developed 15+ backend microservices in a team of 10+ to deliver an internal resource management system to a client with 1000+ resources - Debugged a React app to improve load times by 2x using network waterfall analysis, and fixed latency-prone CSS - Designed complex databases and kept query load times <500ms across all microservices by schema normalization, and query optimization - Improved deployment efficiency by 80% using Python scripts to automate migration tasks

- Collaborated in a team of 3 to develop a Node.js API and React frontend for an employee management system in a research lab. - Implemented a Python-based face detection system with a Siamese Neural Network, deployed via Flask, for employee attendance tracking - Utilized MongoDB to manage and coordinate system data

- Trained as a novice Data Science Engineer by learning Python libraries such as NumPy, Pandas, Matplotlib, Keras. - Learned basic model fitting techniques by completing Andrew Ng’s Machine Learning course offered by Stanford Online on Coursera - Prepared basic PowerBI reports to understand company’s customer data

Grade: 3.47 CGPA. Equivalent to 1.8 (German Grade) Dean’s Honor List semesters 4,5,7 & 8