About Rick
Ingénieur diplomé, Data Scientist. Je suis en particulier intéressé par le traitement de langage naturel ainsi que l'étude des séries temporelles. Pour plus d'informations je serais ravi de vous en parler plus au cours d'un entretien
English
Native or bilingual
Japanese
Conversational
French
Native or bilingual
Remote only
Primarily works remotely
Experience
- Dassault AviationData ScientistAVIATION AND AEROSPACESeptember 2019 - February 2020 (6 months)Istres, FranceMission en régie :Post flight test data analysis project on aircraft sensors- Design of a proof of concept on pre-sale, response to the call for tenders on technical part- Statistical data analysis, signal processing, implementation and definition of signal characteristics with numerical analysis- Implementation of a pattern recognition solution based on recognized temporal characteristics- Comparative study between statistical and signal processing models (Fourier transform, Savitzky filter)- Implementation of a probabilistic temporal anomaly detection model (Bayesian inference) with Markov chain Monte Carlo methods (MCMC) and stochastic processTools : Numpy, Pandas, PyMC3, Tensorflow Probability
- HCube ConseilData ScientistTECHJanuary 2019 - June 2020 (1 year and 5 months)Paris, FranceMissions au forfait :Spatial data analysis project for a planning consulting firm :- Spatial Data Analysis for GIS systems working on vector and raster layers of French cadastral maps- Automation of feature management with implementation of QGIS 3 plugins and standalone Python applications with GeoPandas, GeoDjango and PostGIS- PostgreSQL database setup and configuration on Linux- Multivariate data modeling and analysis between vector layers, aggregation and synthesis of attribute feature insightInternal R&D project for medical radiological image classification:- Research paper documentation and comparison of state-of-the-art existing solutions.- Algorithm implementation of neural network architectures with PyTorch.- Fine-tuning and model optimization with Transfer Learning.- Model benchmarking and performance evaluation of the implemented architectures towards research papers.- Backend model integration app implemented in Flask and Frontend visual implemented with React.js and Node.js
- Laboratoire de recherche en gestion des risques intégrés - ESTP ParisIngénieur developpement RiskRESEARCHFebruary 2018 - Today (8 years and 4 months)Cachan, FranceDeveloppement de stratégies de trading algorithmique en Python, implémentation d'outils statistiques en machine learning pour des séries temporelles sur des cours d'actions.Data visualisation et analyse de donnée avec numpy et pandas. Simulation de monte-carlo sur des scénarii d'allocation de ressources sur des portefeuilles d'actifs.
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Education
- Machine learningStanford University - Coursera2017Certification en Machine learning par Andrew Ng - apprentissage en Matlab
- SQL for Data ScienceUniversity of California - Coursera2018