Cyril Esnault
Data AnalystAI 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
Medical Data Science Lead
I am a Data & Statistical Scientist Lead in the Medical Evidence & Data Science Unit at Roche France. With an engineering background at the intersection of life sciences and statistics, I specialize in data strategy and advanced analytics, spanning both biostatistics and machine learning. I have published research on algorithms for credible subgroup discovery, disease phenotyping (clustering), cross-country outcome transportability, and the robustness of indirect treatment comparisons. My current work focuses on real-world evidence in oncology and the development of innovative clinical research methodologies.
Université Rennes 2
Master's degree, Statistiques appliquées
January 1, 2013 – January 1, 2014
L'Institut Agro Rennes-Angers
Ingénieur, Biologie, environnement et agronomie, général
January 1, 2011 – January 1, 2014
Jean-Baptiste Say
Classes préparatoires
January 1, 2009 – January 1, 2011
Roche
Data Science & BioStatistics Lead - Medical Evidence & Data Science Unit
February 1, 2021 – Present
Quinten
Lead Health Data Scientist
September 1, 2018 – February 1, 2021
Quinten
Senior Data Scientist - Statistic & Machine learning
September 1, 2016 – September 1, 2018
Quinten
Data scientist
September 1, 2014 – August 1, 2016
INSERM
Ingénieur Statisticien (SFE)
March 1, 2014 – August 1, 2014
Région de Paris, France
Cyril Esnault
January 1, 2014 – Present
Comparaisons de méthodes de pénalisation dans le cadre d'études d'association pangénomique (GWAS) Identifier les meilleures méthodes de détection des variants génétiques (SNPs) associés à une maladie (ex sur la Maladie de Crohn) * Simulation de profils génétiques (phénotype/génotype) par modèles logistiques * Modèles avec pénalisations innovantes (sPLS-DA, Sparse-groupe-LASSO, ...), ...
Cultural Fit Analysis
The candidate has a strong background in health data science, which aligns well with roles in the biomedical or pharmaceutical industry. The project descriptions and work history show a consistent focus on applying data science to real-world health problems. However, the project diversity outside of the health domain is limited, which might be a consideration for roles requiring broader industry exposure. The progression through roles at Quinten from Data Scientist to Lead Health Data Scientist demonstrates commitment and growth within an organization.
Soft Skills & Operational Fit
The candidate's experience descriptions highlight leadership, mentorship, and strategic involvement (e.g., 'Member of the Executive Committee', 'Expertise stratégie data & machine learning'). This suggests strong soft skills in leadership, communication, and strategic thinking, which are crucial for senior roles. The focus on R&D activities and innovative methodologies indicates a proactive and growth-oriented mindset.