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R&D Data Science Group Leader M/F

Verkor

Verkor

Data Science
Grenoble, France
Posted on Mar 13, 2026

About this role :

  • The group leader oversees:
  • - A Data Science & Data Analysis team (Insights, modelling, experimentation)
    - An R&D Prototyping Engineering team (Proof of concept software, technical validation)
  • This role focuses on innovation, feasibility, and validation, not long-term production ownership.

Main responsibilities :

  • Leadership & Team Management
  • Lead, mentor, and grow a team of data scientists, data analysts, and R&D/prototyping engineers
  • Set technical direction, priorities and ways of working
  • Foster collaboration between analytical and engineering profiles ·
  • Foster collaboration with CAE team by giving them inputs to build reduced order models for process
  • Ensure high standards of quality, rigor and documentation
  • Strategy & Prioritization
  • Define and manage the R&D and analytics roadmap aligned with business objectives
  • Prioritize initiatives based on, business value, technical feasibility and time to impact
  • Balance exploratory research with delivery of concrete outcomes
  • Data Science & Analytics Oversight
  • Data Exploration and Analysis
  • Predictive & statistical modelling
  • Ensure insights and models are actionable and decision-oriented.
  • R&D Software Prototyping Oversight
  • Oversee development of working prototypes that demonstrate feasibility and validate technical approaches
  • Ensures prototypes are reproducible, well documented, and sharable with digital/IT teams
  • Cross-Functional collaboration
  • Act as a key interlocutor with business stakeholders, the product and process R&D team, and the digital/IT teams.
  • Ensure smooth handover of validated concepts to production teams

Requirements :

  • Masters or PhD in Data Science/Applied mathematics/Statistics
  • Minimum of 8 years of experience
  • Prior experience in leading multidisciplinary technical teams
  • Strong understanding of statistical and machine learning models
  • Large-scale data analytics
  • Familiarity with modern analytics and prototyping stacks
  • Ability to assess technical feasibility and risks
  • Ability to align diverse profiles towards shared goals
  • Strong ability to translate complex findings into business insights
  • Comfortable communicating with senior stakeholders
  • Strategic mindset with a focus on impact