Cusomter Support Specialist & Software Developer

Programmed and configured automation systems in environments specifically designed by vendors and using advanced programming languages. Gained practical experience using data processing technologies, including Data Management, Artificial Intelligence, and Cloud Computing, to analyze and improve the performance of processes. Collaborated with team members to develop applications for intelligent processing lines, utilizing optimization algorithms. Developed an application for inventory management and ensuring efficient stock control, using databases. Programmed a robotic arm on a production line to assemble various parts.

Provided technical assistance and troubleshooting for hardware, software, and network issues to ensure smooth operations. Assisted customers and employees with IT-related inquiries, improving system usability and satisfaction. Managed user accounts, permissions, and system access in accordance with company policies. Documented and resolved support tickets efficiently, maintaining a high resolution rate.

Developed a banking application based on Java that simulates banking transactions and operations, including account creation, deposits, withdrawals, fund transfers, and balance inquiries. Created a transaction management system to perform multiple operations in a practical and efficient manner.

Developed a full-stack web application that allows users to discover others attending the same events. Created a clean, responsive interface with event listings, user cards and a matching dashboard with smooth animations. Implemented JWT login/registration and protected routes, with MongoDB storing user data and event preferences. Developed logic to connect users based on shared events, with profile compatibility indicators and a swipe-style interaction.

Extracted and analyzed data from various datasets using Python. Implemented PCA (Principal Component Analysis) and HOG (Histogram of Oriented Gradients) for feature extraction and reduction. Trained MLP (Multi-Layer Perceptron) models for image classification, achieving an accuracy of up to 89.47%.