Data Scientist - Lutte contre la Désinformation
@ Airbus

Paris, Ile-de-France, France
€40,000
On Site
Full Time
Posted 1 day ago

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Job Details

Overview

Airbus invites motivated candidates to join its Data Science team at Airbus Defence and Space in Elancourt. This internship offers an opportunity to work on multi-source intelligence tools focusing on fake news detection, entity framing, and narrative identification in press articles.

Key Responsibilities

  • Research and implement machine learning techniques and prompt engineering.
  • Extract and classify entity framing from news articles.
  • Develop classification and generation models using NLP methods (BERT, LLMs).
  • Benchmark and evaluate models based on performance, cost, and bias.
  • Collaborate within a team of data scientists to share best practices.

Required Skills and Tools

  • Proficiency in Python and deep learning frameworks (PyTorch, LoRA).
  • Experience with Docker, Gitlab, and DVC.
  • Familiarity with NLP, LLMs, BERT, DeBERTa, HuggingFace, and Mistral.
  • Strong competencies in data science and AI techniques.
  • Advanced English and fluent French language skills.

Internship Details

This 6-month internship, starting around March-April 2026, is designed for candidates pursuing a Bac +5 degree in Data Science or related fields. Eligibility for security clearance is required.

Key skills/competency

  • Data Science
  • NLP
  • Deep Learning
  • Python
  • Model Evaluation
  • LLM
  • BERT
  • Research
  • Classification
  • Bias Analysis

How to Get Hired at Airbus

🎯 Tips for Getting Hired

  • Customize your resume: Emphasize relevant data science projects.
  • Showcase NLP skills: Highlight experience with BERT and LLMs.
  • Prepare technical demos: Include Python and PyTorch examples.
  • Research Airbus culture: Understand their innovation approach.

📝 Interview Preparation Advice

Technical Preparation

Review Python coding standards and libraries.
Practice building models with PyTorch and Docker.
Study BERT, DeBERTa, and LLM architectures.
Benchmark model efficiency and bias evaluation methods.

Behavioral Questions

Describe a challenging team project experience.
Explain your approach to solving technical problems.
Discuss handling feedback during project iterations.
Share a time you managed deadlines under pressure.

Frequently Asked Questions