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Amal Rhimi

@amalrhimi

Data Scientist at Orange Tunisia who developed a recommendation engine and personalized SMS campaigns with LLMs.

At Orange Tunisia, I developed a customer data enrichment pipeline, performed segmentation, and used multimodal AI to extract information from images. I also developed a recommendation engine, generated personalized SMS campaigns with Qwen and Mistral, and created an AI assistant and Power BI dashboards.

My project work includes a knowledge graph-based recommendation system for project risk management, a RAG pipeline for document-based recommendations, and machine learning models for air quality health prediction, trading forecasts, and fraud detection. I also implemented Mask R-CNN for object detection and instance segmentation in optical remote sensing images.

Experience

Work history, roles, and key accomplishments

Content-Based Recommendation System Developer

TenStep Tunisia

Jan 2025 - Present (1 year 10 months)

Designed a Knowledge Graph-based recommendation system for project risk management and developed a RAG pipeline with knowledge extraction from PDF documents using NLP and GNNs.

Python scikit learn TensorFlow NLP PDF Processing Keyword Extraction Knowledge Graphs graph neural networks RAG Lang Chain Pandas NumPy Neo4j

Data Science Intern

Orange Tunisia

Jan 2025 - Present (1 year 10 months)

Developed a web scraping and data enrichment pipeline, performed customer segmentation using VB-GMM, GMM, KNN, and Louvain, and leveraged Qwen-VL for multimodal AI. Built a recommendation engine and generated personalized SMS campaigns using Qwen and Mistral LLMs, and designed an AI assistant and Power BI dashboards.

Python Pandas NumPy scikit learn Flask Power BI Lang Chain RAG Ollama Qwen Qwen VL Mistral GMM VB GMM KNN Louvain Web Scraping Neo4j OCR

Data Scientist

Value Digital Services

Jan 2024 - Present (2 years 10 months)

Developed Machine Learning and Deep Learning predictive models for stock market performance forecasting, integrating sentiment analysis, and designed investment portfolios based on six strategies.

Python scikit learn Machine Learning Random Forest XGBoost LightGBM Pandas NumPy data preprocessing Feature Engineering

Computer Vision Engineer

Esprit Tunisia

Jan 2024 - Present (2 years 10 months)

Implemented Mask R-CNN to improve object detection and instance segmentation accuracy in optical remote sensing images.

Python PyTorch Mask RCNNs Computer Vision Deep Learning OpenCV

Machine Learning Engineer

Environmental Engineering and Eco-Technologies Research Labo

Jan 2024 - Present (2 years 10 months)

Developed Machine Learning and Deep Learning models to predict the impact of air pollution on cardiovascular and respiratory diseases, and analyzed environmental and health data through interactive dashboards.

Python scikit learn KNN Radio Frequency SVM XGBoost LightGBM Deep Learning deep neural networks LSTM GRU Pandas NumPy Power BI Data Visualization TensorFlow

Machine Learning Engineer

BNA Assurances

Jan 2023 - Present (3 years 10 months)

Designed and developed a Machine Learning model for detecting and predicting fraudulent activities, and performed data preprocessing and analysis to improve model performance.

Python scikit learn Imbalanced Learn (SMOTE)Random Forest Balanced Random Forest XGBoost LightGBM Fraud Detection