Badges
Certifications
Work Experience
DATASCiENTiST- STELLANTiS
ExpleoGroup•  September 2022 - Present•  Montigny-le-Bretonneux, France
• Application of a complete end-to-end object detection pipeline to verify the outside conformity of cars after assembly in the factory, with more than 100 classes and achieving a mean Average Precision (mAP) generally exceeding 97%. – Image acquisition and integrity verification. – Image annotation for model training with Label Studio. – Training the RetinaNet model on a GPU cluster on AWS. – Using JFrog Artifactory to store the model. – Using TeamCity to create Docker images necessary for deployment. – Edge deployment of the model in the factory. – Performance analysis of the deployed model. • Migrated the code used for validating the performance of a model on production images before deployment to a new GPU cluster dedicated to data scientists, due to the change in CUDA access methods. The new setup required using a Docker image with CUDA pre‑installed. Created an Enroot image (.sqsh) from the Docker image to run the validation code on the new cluster using a batch script with SLURM. • Developed exception handling for a Streamlit application for Data Scientists. used for creating datasets and dashboards, verifying the integrity of configuration files, etc. • Created pre‑commit hooks to ensure linting with mypy, isort, black and flake8. • Developed unit tests for the Streamlit application with pytest.
DATASCiENTiST- ZODiACFLUiDRA
ExpleoGroup•  April 2022 - June 2022•  Montigny-le-Bretonneux, France
• Create a Pygame simulator to simulate a robot that cleans swimming pools with different shapes following a series of predefined directions. • Train a Reinforcement Learning Agent to find the best directions to take by the robot to maximize the pool coverage for any pool shape and for any initial position using Proximal Policy Optimization algorithm. • Hyperparameter tuning using Optuna. • Frameworks : Pygame, OpenAI Gym, Stable Baselines3, Optuna, MLflow.
DATASCiENTiST- PSA
ExpleoGroup•  September 2021 - March 2022•  Montigny-le-Bretonneux, France
• Develop predictive maintenance tools for a car manufacturer (PSA) for its electric cars’ traction battery : – Cleaning and analyzing data using PySpark. – Nominal Health Monitoring (using an unsupervised anomaly detection algorithm : Local Outlier Factor) – Predict traction battery failure typology using machine learning models (XGBoost, etc.) • Explain machine learning models using Shapley values.
DATAANALYST- RENAULT
ExpleoGroup•  January 2017 - February 2021•  Montigny-le-Bretonneux, France
• Analyze Renault’s electric cars after‑sales incidents involving electric motors and traction batteries (mainly Zoé). • Aggregate various statistics to determine the severity of each incident. • Model the failure using a statistical model (Weibull) to determine its economic cost by estimating the total number of cars that would be impacted by the failure.
END-OF-STUDiESiNTERNSHiP
ArevaNP•  April 2016 - September 2016•  La Défense, France
• Probabilistic modeling of the wear of nuclear power plants’ steam generators’ tubes. • Sensitivity analysis : estimating the importance of the wear model’s parameters using variance decomposition (Sobol indices).
Education
AJC Formation
MACHINE LEARNING ENGINEER PROFESSIONAL BOOTCAMP & PCAP (CERTIFIED ASSOCIATE IN PYTHON PROGRAMMING)•  March 2021 - August 2021
Taught subjects : Linux, Docker, Ansible, SQL, NoSQL, AWS, Azure, Hadoop, Spark, Java, Python, Machine Learning, Deep Learning.
ENSTA ParisTech- École Nationale Supérieure des Techniques Avancées
ENGINEERIN DEGREE•  September 2013 - September 2016
FOCUS ON : APPLiED MATHEMATiCS, PROBABiLiTY AND STATiSTiCS, MECHANiCS
IPEIT- Preparatory Institute for Engineering Studies of Tunis
CLASSES PRÉPARATOIRES AUX GRANDES ÉCOLES D’INGÉNIEURS- CPGE (MATHEMATICS-PHYSICS)•  September 2012 - June 2013
IPEST- Preparatory Institute for Scientific and Technical Studies
CLASSES PRÉPARATOIRES AUX GRANDES ÉCOLES D’INGÉNIEURS- CPGE (MATHEMATICS-PHYSICS)•  September 2011 - June 2012
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