Data Scientist & Digitalization Engineer – System Standard Parts

About the role

Airbus is pioneering sustainable aviation and the System Standard Parts team is accelerating the digital transformation of its engineering cycle. We are looking for a Digitalization Engineer to lead the digital evolution of qualification processes, bridging current ways of working with advanced AI solutions.

Key responsibilities

• Drive the application of data science across the domain, focusing on unstructured data such as technical reports and specifications.
• Develop Generative AI and NLP solutions using Large Language Models for document classification, automated text analysis, and information retrieval.
• Conduct thorough evaluation and statistical analysis of LLMs and other machine‑learning models to ensure performance and reliability.
• Create rapid visualisations and demos to communicate complex findings to engineering stakeholders.
• Engineer prompts and optimise workflows to maximise LLM output quality for technical use cases.
• Champion continuous upskilling and knowledge‑management initiatives aligned with Airbus digital strategy.
• Support the creation and maintenance of a knowledge database in line with Airbus KM goals.
• Engage with cross‑functional teams (Design, Certification, Manufacturing) to understand requirements and provide analytical support.

Required profile

• Bachelor’s or Master’s degree in Computer Science.
• 5‑8 years of professional experience in digitalisation or engineering data science.
• Experience with Design of Experiments and statistical software (e.g., JMP, Minitab, Python libraries).
• Proven track record of developing and deploying machine‑learning models in an engineering or manufacturing context.
• Proficiency in Python (SciPy, Scikit‑learn, TensorFlow/PyTorch) and JavaScript/Apps Script.
• Capability to build enterprise‑level solutions with Google AppSheet and manage Google Cloud/Workspace integrations.
• Strong networking skills with universities, research centres and external partners.
• Excellent communication skills; exposure to Electrical, Mechanical or Aerospace Systems Engineering is a plus.

Required skills

• Python (SciPy, Scikit‑learn, TensorFlow, PyTorch)
• JavaScript / Apps Script
• Google AppSheet
• Google Cloud Platform
• Large Language Models (LLMs)
• Natural Language Processing (NLP)
• Prompt engineering
• Statistical software (JMP, Minitab)
• Design of Experiments

What we offer

• Diverse international team with agile, open‑minded management.
• Work at the intersection of engineering and advanced analytics in an aerospace environment.
• Dynamic, fast‑paced business where your expertise directly impacts daily operations.
• Continuous growth opportunities supported by professional training and a knowledgeable network.