Role Overview

The Job Holder will act as a Data Scientist on Air System applications with the task to provide safe and balanced designs in face of opposing interests and multiple, sometimes conflicting constraints, like Performance, Cost, Environmental, Industrial and Operational Requirements.

The Job Holder will play a key role in developing machine learning and deep learning based models, for predictive and prescriptive decision-making, using in-service data and design data, while being able to build analytics dashboards to analyze aircraft (Air-systems) operational reliability. The Job Holder needs to provide a link between the Air Systems and other groups at Airbus that perform Data Analytics, Predictive Maintenance and gather data from Airbus databases/tools (Skywise / Palantir), to create business intelligence.

Responsibilities

Understand and translate business needs into statistical, machine learning, or AI problem spaces.
Collaborate with IT and Data Analysts to extract and integrate structured and unstructured data from various sources.
Work closely with Data Engineers to design scalable data pipelines and ensure efficient data flow for model training and evaluation.
Analyze data properties and apply scientific methods to propose or develop solutions using statistical, machine learning, or AI techniques.
Design and execute controlled experiments to identify and validate optimal solutions.
Implement solutions using state-of-the-art algorithms and software engineering best practices.
Create monitoring protocols to ensure models align with evolving business needs.
Contribute to the development and reusability of industrial-grade AI solutions.
Share best practices, insights, and techniques with the wider data community.
Ensure compliance with all external and internal regulations and standards.
Develop solutions responsibly in line with Airbus ethical AI principles.

Requirements

Machine learning, Deep learning code development and deployment
Dashboarding in Skywise environments and standalone tools
Experience in building NLP, Time series, Computer Vision & physics based surrogate models
Data driven and hybrid (physics + data) modeling based decision science
Experience in Management of different stakeholders: Customers (Programs, Customer Service), Stakeholder from different functions (other Engineering teams, Procurement, Production, Customer Service, Quality, Config Mgmt)
Masters or Bachelors degree in Aerospace/Mechanical/Applied Math or related streams.