Data Scientist

Airbus India Innovation Centre (AIC) is at the forefront of the company’s 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. In this fast-paced environment, the Innovation Team acts as an internal incubator for disruptive technologies. Our projects follow a rigorous lifecycle from Proof of Concept (PoC) to full industrial deployment. To support these goals, AIC seeks to onboard a Data Scientist to explore ill-defined complex business problems around data using scientific methods and to transform them into insights solutions based on state of the art machine learning, AI and statistics with the focus on forward-looking applications. The Data Scientist will work closely with AI lead and Product Managers to ensure data integrity throughout the product life cycle.

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

Bachelor’s degree in a quantitative technical field (Data Science, Statistics, Mathematics, or Aerospace Engineering); 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; 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); Practical knowledge of containerization and cloud/on-premise deployment to ensure models move from research to production; 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; AI: Machine Learning & Deep Learning - Advanced Level; Artificial Intelligence (AI) Approaches - Advanced Level; Applied probabilities & Statistics - Advanced Level; Software engineering fundamentals - Autonomous Level; Data Governance Management System - Autonomous Level; Data Science: Advanced Analytics - Advanced Level; Data Science: Data visualisation & Coms - Advanced Level; Data Science: Data Wrangling - Advanced Level; Data Security - Basic Level; Generative AI Essentials & Prompting - Advanced Level; Eco-design & Sustainability of Digital services - Autonomous Level

Nice to have

Master’s or Ph.D. in a quantitative field (e.g., Physics, Mathematics, Aerospace Engineering, or Computer Science); Hands-on experience with Physics-Informed Neural Networks (PINNs) and hybrid modeling approaches; Subject matter expertise in aviation datasets (flight data, maintenance records, passenger telemetry) and business processes

Benefits

Flexible working arrangements