As a Data Science Researcher at Laboratoire RIADI, I used Auto-encoder to extract features from data to make recommendations. I developed a hybrid recommendation approach based on the features extracted by the convolutional auto-encoder. I worked with various tools such as Deep Learning, Python, etc. Previously, I was a Full Stack Developer at GreenCode Engineering, where I collaborated on the main project in a team-based, agile environment to implement and maintain use cases based on the client’s requests. I developed full-stack web and mobile applications, and worked closely with the team to determine problems. I have a master's degree in data science from the National School of Computer Science - (ENSI), and a bachelor's degree in computer science from the Higher Institute of Information Technologies and Communication. I am highly motivated and passionate about data science and development, and eager to start a career and apply my skills and knowledge. I have strong teamwork, flexibility, adaptation, autonomy, and creativity skills, and I am always willing to learn new technologies and methods. My goal is to contribute to innovative and impactful projects that can solve real-world problems and improve people's lives.