About Benoit
English
Fluent
French
Native or bilingual
Spanish
Basic
Experience
- SchlumbergerData ScientistENERGY AND UTILITIESJuly 2019 - March 2020 (8 months)Houston, United StatesCement thickening time prediction:• Optimization of the preprocessing pipeline: 8 times faster• Build dashboard to control data quality• Clustering of experiments and outlier detection• Build regression model with confidence estimation: reduce errorsby 25%• Deploy user-friendly webapp dividing the time needed to find theoptimal cement recipe by 30Maintenance cost prediction:• Build a constrained linear regression modelSubsurface fiber optics responses prediction:• Unsupervised pretraining using infoVAE on 30M data points• Expected savings $1M/well
- Bearing pointData ScientistENERGY AND UTILITIESSeptember 2018 - June 2019 (10 months)Paris, FranceOptimization of the energy consumption of a silicon furnace:• Data analysis and visualisation to identify causes of decline in siliconproduction• ARMA model to anticipate these drops
- SopraSteriaData scientistDEFENSE AND MILITARYFebruary 2018 - August 2018 (6 months)Courbevoie, FranceTrajectory clustering via deep learning representation using auto-encoder:• Fine tuning parameters• VisualizationOptical character recognition and entities extractions on invoices andmedical prescriptions:• Computer Vision with OpenCV• Natural language processing with NLTK• Deployment with docker
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Education
- IngénieurArts et Metiers Paristech2018Formation ingénieur généraliste avec une spécialisation en système d'informations.
- Mastère spécialiséTélécom ParisTech2020Big data et Machine learning Courseworks Include: - Machine Learning and Statistics - Reinforcement Learning - Deep Learning - Natural Language Processing - Computer Vision - Econometrics and Time Series - Data Engineering (NoSQL / Distributed computation) - Data Visualisation - Web data Projects: - Generation of classical music (J.S Bach alike) from MIDI files with a deep-RNN (LSTM layers) architecture model - Adversarial Examples: Developed a CNN-based model for gender prediction and worked on adversarial examples to mislead the classifier and study the effect of adversarial attacks - Visualization project using data from Grand Débat including the deployment of a front-end interface and iterations between graphs. - Construction of a NoSQL architecture to query on GDELT database (700 GB of data for 2018) using Spark Scala for data pre-processing and MongoDB for queries (on AWS EC2 machines)
Certifications
- Deep Learning A-Z™: Hands-On Artificial Neural NetworksUdemy2018
- Fondamentaux pour le Big DataIMT2018