10/09/2026 updated
100 % available
Data Scientist & AI Engineer
Sfax, Tunisia
Worldwide
Research Master's in Data Science (M2)About me
As a junior AI/ML engineer, I am eager to build a robust portfolio through my experiences.
Artificial IntelligenceData AnalysisGitHubPython (Programming Language)Machine LearningTensorFlowData SciencePyTorchReact.jsDeep LearningGenerative AIConvolutional Neural NetworksBackendKerasFastAPI
Machine Learning & Deep Learning
Expertise in machine learning and deep learning frameworks including Scikit-learn, PyTorch, TensorFlow, Keras, and XGBoost. Development of convolutional neural networks, reinforcement learning systems, and fine-tuned NLP models for real-world applications.
Data Analysis & Visualization
Proficiency in data analysis and visualization tools such as NumPy, Pandas, R, Matplotlib, Seaborn, Power BI, and Plotly. Building interactive dashboards and KPI reporting systems for business insights.
AI Platform Development
Development of end-to-end AI/ML platforms integrating hybrid time-series models, LLM-powered analysis, and recommendation agents, served via FastAPI and React.
Programming Languages
Strong command of Python, R, C/C++, and Java for scientific computing, data engineering, and application development.
Databases
Experience with relational database systems including MySQL, Oracle, and SQLite for data storage, retrieval, and structure optimization.
Computer Vision
Application of computer vision techniques using YOLOv8, DeepSORT, and OpenCV for real-time object detection, tracking, and queue monitoring systems.
Mathematics
Strong foundation in Linear Algebra, Probability, Statistics, and Optimization, applied to modeling and engineering problem-solving.
Version Control
Use of Git and GitHub for source code management, collaboration, and version tracking in software and data science projects.
Full-Stack Web Development
Development of full-stack web applications using React.js and Flask, including analytics dashboards with interactive KPIs and ticket management features.
Expertise in machine learning and deep learning frameworks including Scikit-learn, PyTorch, TensorFlow, Keras, and XGBoost. Development of convolutional neural networks, reinforcement learning systems, and fine-tuned NLP models for real-world applications.
Data Analysis & Visualization
Proficiency in data analysis and visualization tools such as NumPy, Pandas, R, Matplotlib, Seaborn, Power BI, and Plotly. Building interactive dashboards and KPI reporting systems for business insights.
AI Platform Development
Development of end-to-end AI/ML platforms integrating hybrid time-series models, LLM-powered analysis, and recommendation agents, served via FastAPI and React.
Programming Languages
Strong command of Python, R, C/C++, and Java for scientific computing, data engineering, and application development.
Databases
Experience with relational database systems including MySQL, Oracle, and SQLite for data storage, retrieval, and structure optimization.
Computer Vision
Application of computer vision techniques using YOLOv8, DeepSORT, and OpenCV for real-time object detection, tracking, and queue monitoring systems.
Mathematics
Strong foundation in Linear Algebra, Probability, Statistics, and Optimization, applied to modeling and engineering problem-solving.
Version Control
Use of Git and GitHub for source code management, collaboration, and version tracking in software and data science projects.
Full-Stack Web Development
Development of full-stack web applications using React.js and Flask, including analytics dashboards with interactive KPIs and ticket management features.
Experience
Professional experience0 - 5 years
Freelancer since2025
Languages
EnglishFluentFrenchFluent
Project history
Developed an end-to-end AI/ML platform for French electricity price forecasting, integrating hybrid time-series models, LLM-powered news analysis, and an AI recommendation agent, served via FastAPI and React.
Designed and implemented a multi-agent reinforcement learning system (Q-Learning, DQN, PPO) integrated with the SUMO traffic simulator to optimize signal timing, reducing congestion and improving flow efficiency.
Developed and trained a convolutional neural network on chest X-ray images for pneumonia detection, applying data augmentation and model optimization to achieve high diagnostic accuracy.