Data Scientist - Recherche Operationnelle F/H

Thales
France
Workplace: HybridFull timeFunction: Data Science & Machine LearningExperience: 5-7 yearsEducation: mastersSkills: ["Communication","Collaboration","Autonomy","Initiative","Teamwork"]

Design and develop ML/deep learning solutions for defense and critical-industry use cases within the cortAIx AI delivery team. Work from data collection through deployment to end users, analyzing data to select appropriate models and validating algorithms using statistical and mathematical methods. Collaborate across global business units, the AI lab, and clients via workshops, communicating insights and results while supporting MLOps and production-grade model lifecycle.

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FursaFursa
Thales
Thales
4 days ago

Data Scientist - Recherche Operationnelle F/H

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 11 hours agoStatus: Live
Reposted: similar role first listed 5 months ago

Job Summary

Design and develop ML/deep learning solutions for defense and critical-industry use cases within the cortAIx AI delivery team. Work from data collection through deployment to end users, analyzing data to select appropriate models and validating algorithms using statistical and mathematical methods. Collaborate across global business units, the AI lab, and clients via workshops, communicating insights and results while supporting MLOps and production-grade model lifecycle.
Location: France
Workplace: Hybrid
Employment Type: Full time · Permanent
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Participate in identifying AI needs with different Thales branches and clients through ideation workshops, proposing tailored algorithmic solutions.
  • •Analyze available data quickly to choose the most relevant AI models for identified challenges and use cases.
  • •Develop, test, and validate data processing algorithms using statistical, mathematical, and machine learning methods for varied technical environments.
  • •Support model lifecycle and deployment (MLOps) to production usage, including end-to-end solution delivery.
  • •Share project insights and communicate successes, learnings, and progress internally and externally.

Key Requirements

  • •Master 2 (BAC +5) from an engineering school or equivalent university degree.
  • •Minimum 5 to 7 years of practical experience in AI and ML solution deployment.
  • •Experience implementing embedded Machine Learning solutions from data collection to production deployment for users.
  • •Strong statistics and ML/DL knowledge, including model communication with non-expert stakeholders.
  • •Proficiency with TensorFlow and PyTorch, plus Python; GitLab and Docker and MLOps familiarity are expected.
Experience:5-7 years
Education:Master's
Skills:CommunicationCollaborationAutonomyInitiativeTeamwork
Tech Stack:PythonTensorFlowPyTorchJavaSparkScalaGitLabDockerMLOpsMachine LearningDeep Learning

Eligibility

Security Clearance:Secret de la défense nationale

Company Brief

Thales
Designs and delivers advanced systems and services for aerospace, defence, security, and digital identity and cybersecurity markets, serving government and commercial customers worldwide.
Industry: Defense Technology
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Paris, France
Founded: 2000
WebsiteLinkedIn