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Deep Learning Scientist
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
I have a PhD in Machine Learning / Deep Learning (specialized in reinforcement learning) from Sorbonne Université, and I worked on various applications, from natural language processing to time series and images. I am interested in everything related to artificial intelligence, and I’m not confined to research – I also like to think about how IA can be used to improve things, and how to implement it.
Pierre and Marie Curie University
Master's degree, Machine Learning (spécialité DAC)
January 1, 2013 – January 1, 2015
Université de Poitiers
Master's degree, Mathématiques
January 1, 2009 – January 1, 2011
Université de Poitiers
Licence, Mathématiques
January 1, 2008 – January 1, 2009
Safran.AI (ex Preligens)
Deep Learning Scientist
January 1, 2025 – Present
Paris, Île-de-France, France
AnotherBrain
Ingénieur IA
February 1, 2021 – October 1, 2023
Groupe Caisse des Dépôts
Data Scientist
December 1, 2019 – June 1, 2020
Paris, Île-de-France, France
Aquila Data Enabler
Consultante data scientist
October 1, 2019 – February 1, 2021
Laboratoire d'Informatique de Paris 6
Doctorant en machine learning
October 1, 2015 – May 1, 2019
Laboratoire d'informatique de Paris 6 - Sorbonne Université
Laboratoire d'Informatique de Paris 6
Stagiaire recherche - machine learning
March 1, 2015 – August 1, 2015
Laboratoire d'informatique de Paris 6 - Sorbonne Université
Laboratoire d'Informatique de Paris 6
Stagiaire recherche - représentation des connaissances
June 1, 2014 – July 1, 2014
Laboratoire d'Informatique de Paris 6 - Sorbonne Université
Education nationale
Professeur certifié stagiaire de mathématiques
September 1, 2012 – August 1, 2013
Lycée Cordouan de Royan
Cultural Fit Analysis
The candidate has worked in diverse environments, from academic research to startups (AnotherBrain, Aquila Data Enabler) and larger corporations (Groupe Caisse des Dépôts, Safran.AI). This breadth of experience suggests adaptability to different company cultures. The focus on ML/AI roles aligns well with the target role of ML Engineer. However, the lack of explicit project diversity beyond core ML applications limits a deeper assessment of cultural fit.
Soft Skills & Operational Fit
The candidate's experience descriptions indicate an ability to manage client interactions, foresee tasks, resolve bugs, and work within agile methodologies. This suggests good operational fit and communication skills for project execution. However, without specific soft skill assessments, this remains an inference.