Data Scientist

The Airbus India Innovation Centre (AIC) is at the forefront of the companys digital transformation, particularly within the Innovation and Engineering departments. As we move towards Industrialisation of AI, the department focuses on applying Advanced Analytics, Machine Learning, and Deep Tech to solve critical aerospace challenges—ranging from generative design and predictive maintenance to autonomous systems Role & 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

Education and Experience:

• Education: Bachelors degree in a quantitative technical field (Data Science, Statistics, Mathematics, or Aerospace Engineering). A Masters or Ph.D. in a quantitative field (e.g., Physics, Mathematics, Aerospace Engineering, or Computer Science) is an advantage.
• Industry Tenure: 8+ years of experience in data-related roles, with a proven track record of leading technical teams through the full AI project lifecycle.
• Advanced knowledge of modern architectures, including CNNs and Transformers.
• Hands-on experience with Physics-Informed Neural Networks (PINNs) and hybrid modeling approaches is an advantage
• Proficiency with GenAI toolkits such as Hugging Face, LangChain, and LlamaIndex, alongside agentic frameworks (e.g., Google ADK).
• Expert-level coding in Python and deep familiarity with the ecosystem (PyTorch, TensorFlow, Scikit-learn).
• Expert knowledge of SQL and database systems (PostgreSQL, MySQL, Oracle), including terminal-based workflows (e.g., Claude Code).
• Subject matter expertise in aviation datasets (flight data, maintenance records, passenger telemetry) and business processes is definite advantage
• Practical knowledge of containerization and cloud/on-premise deployment to ensure models move from research to production.
• The ability to translate complex model outputs into "The Story Behind the Data" for non-technical global stakeholders.
• Ability to operate within a Quality Management System (QMS), ensuring all code and research is reproducible, audit-ready, and meets "aircraft-grade" standards.
• Comfortable with a "fail-fast" innovation mindset while maintaining the rigorous safety and quality requirements of the aerospace industry.
• Experience working cross-functionally with AI Engineers and Product Managers for End-to-End delivery.