Libraries and Frameworks: Matplotlib, Seaborn, Plotly, Pandas, Numpy, SciPy, Scikit-Learn, Prophet, Darts, Pytorch, Tensorflow, Keras, Spacy, nltk, Hugging Face, FastAPI, Streamlit
- M.S. (bac +5), Computer Science (Data Science and Analytics track) | EPITA (April 2023)
- B.S. (bac +3), Computer and Communication Engineering | LIU (August 2021)
AI Engineer @ Helean (_Octobre 2022 - _April 2023)
- Conducted data analysis on huge Time Series client financial datasets to gain insights and inform decision-making processes.
- Extracted relevant information from large datasets to identify patterns and trends; it includes data mining.
- Contributed to the development of machine and deep learning models, as well as the creation of a basic recommender system model for customers (event description analysis using NLP techniques and word embeddings using Spacy, nltk, Camembert, flair).
- Worked with PyTorch, Scikit-learn, and TensorBoard for model development and optimization.
- Contributed to data processing pipelines for data ingestion, transformation and feature engineering.
- Used data visualization tools (Jupyter, Pycharm, VScode, Matplotlib, Seaborn, Pandas and Excel) to present findings and communicate results to the founders
