Data scientist @ Data Prisme 2021-2023

• Optimizing stock management using Deep Reinforcement Learning algorithm
• Implementation of new models in production
• Improvement of a simulation tool to validate a model prototype.
• Set up of our own cluster to distribute our computations and data.
  [Ray, MinIO, Sklearn, Scipy, Poltly, Ansible, Airflow, Drone CI, Pytorch]

Data Engineer Consultant @ Orange 2021-2022

• Took part in the implementation of a data lake at Orange Reunion (mobile operator). [Hadoop, Spark, Python, Hive, NetworkX]

Machine Learning Engineer @ INRIA 2019-2020

Airplanes trajectory optimization to reduce CO2 emissions.

• Creation of an open source library to optimize any type of trajectories. See examples here
• Participation in a publication. See preprint.
• Optimizing code source execution using vectorisation, parallel computing, numba compilation and finally a cluster. [Python, Dash, Travis CI, Numba, Linux, Scikit-Learn]

Data science intern @ Aliri 2019

• Computer science applied to mass spectrometry imaging
• Collaboration with biologists, chemists and Aliri customers.
• Creation of a biomarker discovery tool for medical and pharmaceutical research. [Python, C, API design, OpenCV, Parallel programming, Deep Learning]

Data science intern @ Exoclick 2018

• Creation of a Deep Learning model to automatically classify ads in order to target ads on the network.
• The AWS cloud (SageMaker) was used to earn the model, and the dataset was saved on S3. [Keras, AWS, S3, MySQL]

Symbiome: personal project

• Measuring infected area in beet fields using AI
• Developping a bat counter application

Junia 2014-2019

Master degree (french Diplôme d'ingénieur) in computer science

• 2016: Particule simulation using JavaScript, Taylor polynomials and Coulomb Law.
• 2017: Expression Recognition using deep convolutional neural networks (Inception, Resnet...). Here you can see a demo.