I am a motivated data scientist and full stack developer, constantly learning and eager to contribute to innovative projects. I enjoy turning complex data into actionable insights and building end-to-end web applications that users love. With hands-on experience in medical imaging AI and MERN-stack projects, I value rigor, creativity, and collaboration. I’m looking for a challenging opportunity to grow and make a meaningful impact in a stimulating environment.…

Hani Ben Jemaa Dite Bounagra

I am a motivated data scientist and full stack developer, constantly learning and eager to contribute to innovative projects. I enjoy turning complex data into actionable insights and building end-to-end web applications that users love. With hands-on experience in medical imaging AI and MERN-stack projects, I value rigor, creativity, and collaboration. I’m looking for a challenging opportunity to grow and make a meaningful impact in a stimulating environment.…

Available to hire

I am a motivated data scientist and full stack developer, constantly learning and eager to contribute to innovative projects. I enjoy turning complex data into actionable insights and building end-to-end web applications that users love.

With hands-on experience in medical imaging AI and MERN-stack projects, I value rigor, creativity, and collaboration. I’m looking for a challenging opportunity to grow and make a meaningful impact in a stimulating environment.

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Skills

Experience Level

HTML5
Expert
MySQL
Expert
SQL
Expert
MongoDB
Expert
React JS
Expert
GitHub
Expert
Node.js
Expert
Tailwind
Expert
JavaScript
Expert
Python
Expert
CSS
Expert
Keras
Intermediate
TensorFlow
Intermediate
Java
Intermediate
C
Intermediate
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Language

Arabic
Fluent
English
Intermediate
Spanish; Castilian
Beginner
French
Advanced

Work Experience

Data Scientist - Final Year Internship at Laboratory of Technologies and Medical Imaging, Faculty of Medicine of Monastir
February 1, 2025 - October 1, 2025
Developed deep learning models for classification and segmentation of breast cancer medical images; implemented generative adversarial networks (ACGAN) for medical image classification; developed a U-Net model for precise segmentation of cancerous areas; performed in-depth data preprocessing and quality assurance for training data.
Frontend Developer at Awel
October 1, 2023 - March 1, 2024
UI development with React.js and Material-UI for a modern responsive stock management system; creation and styling of reusable components; collaboration with backend team to integrate REST APIs; adherence to frontend design principles and best practices.
Full Stack Developer - Final Year Internship at ArtGuru
January 1, 2023 - May 1, 2023
Design and development of a complete web application using the MERN stack; frontend with React.js and Tailwind CSS; backend with Node.js and Express.js; MongoDB for data management; implemented secure authentication and user session management.

Education

Master in Data Science at ISIMM - Higher Institute of Computer Science and Mathematics of Monastir
September 1, 2023 - June 1, 2025
Bachelor in Software Engineering at ISIMM - Higher Institute of Computer Science and Mathematics of Monastir
September 1, 2020 - June 1, 2023
Baccalaureate in Computer Sciences at Ibn Arafa high school
January 11, 2030 - January 1, 2020

Qualifications

Add your qualifications or awards here.

Industry Experience

Software & Internet, Healthcare, Life Sciences, Education, Professional Services
    paper Application of Happiness at Work

    • Design and development of a complete web application using the MERN stack
    • Development of the frontend with React.js and Tailwind CSS for a modern and responsive interface
    • Implementation of the backend with Node.js and Express.js to manage RESTful APIs and server logic
    • MongoDB integration for efficie

    paper Anomaly Detection System for Breast Cancer

    Development of deep learning models for the classification and segmentation of medical images related to breast cancer
    • Implementation of generative antagonist networks (ACGAN) for medical image classification
    • Development of a U-Net model for the precise segmentation of cancerous areas
    • In-depth analysis and pre-processing of the medical dataset to ensure training data quality