Freelancer profile translated to English.
Back to original languageAbout Marc
Graduate of Ecole Polytechnique and Ecole Normale Supérieure.
Experience in private research labs: Spotify AI Research Lab and public: MILA (University of Montreal).
Publication of 4 research papers.
Expertise and speed of execution in Python with classic data processing libraries: pandas, numpy, Machine Learning: XGBoost, scikit-learn, tensorflow, keras...
Mastery of classic to cutting-edge machine learning algorithms (Generative Adversarial Networks, Deep Reinforcement Learning, LSTMs, Word2Vec...).
The domains on which I have already carried out missions include:
> Load balancing in the energy sector
> Optimal staffing by predicting call volume for a call center
> B2C churn predictive model for an alternative electricity provider.
> Health - prediction of post-operative risks for cardiology labs in 100+ hospitals in the United States
English
Native or bilingual
French
Native or bilingual
Can work on-site
Paris 4e Arrondissement (up to 10km)
Experience
- CHANEL SAS - Corporate IT - Digital, CRM, CCC
On Malt
Development of a Speech-to-text module on specific vocabularyNovember 2020 - February 2021 (3 months)Paris, FranceDevelopment of an automatic speech recognition module on specific vocabulary.- Creation of an extraction filter for a targeted dataset- Training of a Speech-to-Text model- Training of a Named-entity-recognition model for named entity extraction - Village AICEO - Head of AI LabDIGITAL AND ITMarch 2019 - Today (7 years and 4 months)Paris, France
- SpotifyAI Research ScientistFILM AND AVJanuary 2018 - March 2019 (1 year and 2 months)Cité de Londres, United KingdomResearch Scientist specializing in Machine Learning and Audio Signal Processing.- Development of an ensemble method for cover song identification. Patent filed for this new method and scientific publication at the ISMIR conference (International Society for Music Information Retrieval)https://arxiv.org/abs/1905.11700- Development of Deep Learning models for automatic music generation, both raw audio signal generation (Wavenet, ClariNet type models) and symbolic MIDI generation (MusicVAE type models, i.e. Variational Auto-Encoders with hierarchical recurrent network decoders)
Reviews
Julien
CHANEL SAS - Corporate IT - Digital, CRM, CCC
Reviewed on 2/2/2021
Recommendations
FU
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Education
- Polytechnician EngineerEcole Polytechnique2016Cycle polytechnicien, filière Data Science et mathématiques appliquées. Algorithmique, Théorie des Graphes, Recherche Opérationnelle, Randomization, Analyse de données topologique, Apprentissage Statistique
- MVA Master (Mathematics, Vision, Learning)Ecole Normale Supérieure2017Deep Learning, Reinforcement Learning, NLP, Audio Signal Processing, Méthode des noyaux, Object Recognition, Computer Vision, Graphs in Machine Learning