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Computer Vision Engineer at namR
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Grenoble INP - Phelma
Engineer's degree, Signal and Image processing
January 1, 2011 – January 1, 2014
Lycée Albert Schweitzer
PSI*, Physique, Sciences de l'Ingénieur
January 1, 2009 – January 1, 2011
Lycée Jean-Jacques Henner
Baccalauréat, Scientifique, Sciences de l'Ingénieur, option Physique
January 1, 2006 – January 1, 2009
QuantCube Technology
Lead Data Scientist - Remote Sensing
November 1, 2025 – Present
namR
Lead Computer Vision Engineer
January 1, 2023 – October 1, 2025
namR
Computer Vision Engineer
February 1, 2018 – October 1, 2025
IGN (Institut national de l'information géographique et forestière)
Ingénieur traitement d'images et deep learning
July 1, 2016 – January 1, 2018
Saint-Mandé
Trixell (Thales)
Projet de Fin d'Etudes
February 1, 2014 – August 1, 2014
Moirans
GIPSA-LAB
Assistant Chercheur Stagiaire
May 1, 2013 – July 1, 2013
Grenoble
VLYM SA
Cadre technique
July 1, 2007 – August 1, 2010
Extraction automatique de données
January 1, 2013 – May 1, 2013
Projet d'extraction automatique de données de graphiques. Extraction des données graphiques de documents scannés, sous forme de script Matlab. Interface utilisateur, ergonomie et vision "produit commercial".
Cultural Fit Analysis
The candidate's diverse experience across different companies (QuantCube Technology, namR, IGN, Trixell, GIPSA-LAB) and roles demonstrates adaptability. The focus on research and development, particularly in image processing and deep learning, aligns with an innovative and technically driven culture. The project on 'Extraction automatique de données' also shows initiative and a product-oriented mindset. The long tenure at namR (7+ years) suggests loyalty and commitment. The target role of 'Data Analyst' is a slight shift from their primary Computer Vision/Data Scientist roles, but their strong analytical and data processing background makes them a good fit for data-intensive environments.
Soft Skills & Operational Fit
The candidate's experience as a Lead Computer Vision Engineer and Lead Data Scientist suggests strong leadership, project management, and problem-solving skills. The descriptions indicate an ability to manage teams, source data, and develop complex algorithms, which are transferable to operational roles requiring analytical rigor and technical oversight. However, specific soft skill assessments are not available.