Anael Beaugnon
ML EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Full stack data scientist @ Alan
Data Scientist with 9 years of experience. Key strengths: • Successfully deployed machine learning models in production at scale, ensuring their seamless integration into real-world applications. • Proven ability to identify and leverage the most advanced solutions from the literature, staying abreast of emerging trends and methodologies. • Expertise in benchmarking and evaluating models to ensure their efficacy and alignment with business objectives. • Dedicated to promoting best practices around data management, model development, and code optimization. I am always eager to collaborate with innovative teams to solve complex problems using data science, fostering meaningful impact and driving business success.
Ecole normale supérieure
Doctor of Philosophy (PhD), Computer Science
January 1, 2015 – January 1, 2018
University of Melbourne
Postgraduate exchange, Statistics and Computer Science
January 1, 2013 – January 1, 2013
National School of Computer Science and Applied Mathematics of Grenoble
Master's degree, Mathematics and Computer Science
January 1, 2011 – January 1, 2014
Classe préparatoire aux grandes écoles, Lycée du Parc (Lyon, FRANCE)
Mathematics, Computer Science, Physics
January 1, 2009 – January 1, 2011
Alan
Full stack Data Scientist
May 1, 2024 – Present
Paris, Île-de-France, France · Hybrid
Roche
Data Scientist / Operational tech lead
January 1, 2021 – May 1, 2024
Boulogne-Billancourt, Île-de-France, France
ANSSI - Agence nationale de la sécurité des systèmes d'information
Deputy Lead of the Intrusion Detection Research Team
September 1, 2018 – January 1, 2021
ANSSI - Agence nationale de la sécurité des systèmes d'information
Machine Learning Scientist for Computer Security
June 1, 2018 – January 1, 2021
Ecole Polytechnique
Teachning assistant
April 1, 2015 – June 1, 2016
Greater Paris Metropolitan Region
ANSSI - Agence nationale de la sécurité des systèmes d'information
PhD student - Expert-in-the-Loop Supervised Learning for Computer Security Detection Systems
December 1, 2014 – June 1, 2018
Orange
Machine Learning Scientist
May 1, 2014 – November 1, 2014
Issy-les-Moulineaux (Paris area, France)
Ezakus
Data scientist
January 1, 2014 – May 1, 2014
Greater Paris Metropolitan Region
Aupair World
Au pair girl
July 1, 2010 – August 1, 2010
Bunratty (IRELAND)
ABC Languages Au Pair Agency
Au pair girl
July 1, 2009 – August 1, 2009
Castleconnel (IRELAND)
LoisiRiorges
Youth Leadership Certificate in Holiday Camp (BAFA)
January 1, 2009 – June 1, 2009
Riorges (Loire, FRANCE)
Generative Deep Learning with TensorFlow
DeepLearning.AI
June 24, 2026 – Present
Convolutional Neural Networks
DeepLearning.AI
June 24, 2026 – Present
Generative AI with Large Language Models
DeepLearning.AI
June 24, 2026 – Present
Machine Learning (Stanford University, Andrew Ng)
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a strong academic and professional background in Machine Learning and Data Science, aligning well with a technical, research-oriented culture. The experience across various companies, including a government agency (ANSSI) and a large pharmaceutical company (Roche), indicates adaptability to different organizational structures and objectives. The role as 'Full stack Data Scientist' at Alan suggests a willingness to engage across the entire data science lifecycle. The lack of detailed project descriptions makes it difficult to assess collaboration style or specific cultural preferences.
Soft Skills & Operational Fit
The candidate's experience as an 'Operational tech lead' at Roche suggests leadership and operational management skills. Teaching assistant experience indicates an ability to explain complex concepts. The diverse work environments (government agency, pharmaceutical, tech startups) imply adaptability. However, without specific project descriptions or interview data, a detailed assessment of soft skills and operational fit is limited.