Nada Labiadh

Developed an automated data connector for Apidae, synchronizing hundreds of thousands of rows reducing manual intervention by 90%. • Reduced data-loading complexity by implementing bulk processing, refined queries, hashing, and in-memory data handling. This decreased loading time by 78%. • Built a configurable search engine with custom fields, logical filters, multi-criteria sorting, and trigram fuzzy matching for accurate and flexible queries. • Designed and implemented modular front-end templates

Collaborated a scalable backend in Python and Django, powering a platform used by 147 municipalities to digitize systems, reduce administrative complexity, and cut paper waste. • Delivered REST APIs to support 50,000+ users while ensuring scalability for future expansion. • Automated task handling with Celery, RabbitMQ, and Redis. • Deployed and maintained the e-ticketing app using Ansible with real-time error monitoring via Bugsnag, enhancing reliability.

- Worked on an NLP model using Python and PyTorch, achieving 85% accuracy. • Created a Flask API that supported real-time chatbot interactions with healthcare users

• Used React and Django, ensuring a robust and smooth application. • Employed PostgreSQL for database management.

Developed efficient reporting solution using Python, Odoo, XML, Less, and PostgreSQL for robust database management. • Improved system stability and reporting by integrating Power BI, streamlining data analysis for business insights.