Job Description:
The 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.
Job Description:
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
Key Competencies: Competency & Skill Level
AI: Machine Learning & Deep Learning : 3 - Advanced Level
Artificial Intelligence (AI) Approaches : 3 - Advanced Level
Applied probabilities & Statistics : 3 - Advanced Level
Software engineering fundamentals : 2 - Autonomous Level
Data Governance Management System : 2 - Autonomous Level
Data Science: Advanced Analytics : 3 - Advanced Level
Data Science: Data visualisation & Coms : 3 - Advanced Level
Data Science: Data Wrangling : 3 - Advanced Level
Data Security : 1 - Basic Level
Generative AI Essentials & Prompting : 3 - Advanced
Eco-design & Sustainability of Digital services : 2 - Autonomous Level
Competency Scale:
Basic Level: Basic level of expertise, performs routine and/or recurrent tasks, implies partial supervision.
Autonomous Level : Ability to solve problems autonomously, no supervision required in these tasks. Can deal with unforeseen issues.
Advanced Level: High Level of knowledge and wide experience which is internally recognised. Could be a mentor/coach/advisor to support skill development of other colleagues
Education and Experience:
Education: Bachelor’s degree in a quantitative technical field (Data Science, Statistics, Mathematics, or Aerospace Engineering). A Master’s 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.
This job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company’s success, reputation and sustainable growth.
Company:
Airbus India Private LimitedEmployment Type:
Permanent-------
Experience Level:
ProfessionalJob Family:
DigitalBy submitting your CV or application you are consenting to Airbus using and storing information about you for monitoring purposes relating to your application or future employment. This information will only be used by Airbus.
Airbus is committed to achieving workforce diversity and creating an inclusive working environment. We welcome all applications irrespective of social and cultural background, age, gender, disability, sexual orientation or religious belief.
Airbus is, and always has been, committed to equal opportunities for all. As such, we will never ask for any type of monetary exchange in the frame of a recruitment process. Any impersonation of Airbus to do so should be reported to [email protected].
At Airbus, we support you to work, connect and collaborate more easily and flexibly. Wherever possible, we foster flexible working arrangements to stimulate innovative thinking.
Skills Required
- Bachelor's degree in a quantitative technical field (Data Science, Statistics, Mathematics, or Aerospace Engineering)
- 8+ years of experience in data-related roles with proven track record of leading technical teams through full AI project lifecycle
- Expert-level coding in Python and deep familiarity with PyTorch, TensorFlow, Scikit-learn
- Expert knowledge of SQL and database systems (PostgreSQL, MySQL, Oracle) including terminal-based workflows
- Advanced knowledge of modern architectures including CNNs and Transformers
- Proficiency with GenAI toolkits (Hugging Face, LangChain, LlamaIndex) and agentic frameworks (e.g., Google ADK)
- Practical knowledge of containerization and cloud/on-premise deployment for productionizing models
- Ability to operate within a Quality Management System (QMS) ensuring reproducible, audit-ready code and research
- Experience collaborating cross-functionally with AI Engineers and Product Managers for end-to-end delivery
- Ability to translate complex model outputs into clear narratives for non-technical global stakeholders
- Master's or Ph.D. in a quantitative field (Physics, Mathematics, Aerospace Engineering, 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
Airbus Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Airbus and has not been reviewed or approved by Airbus.
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Healthcare Strength — Healthcare coverage is positioned as comprehensive in several locations, including medical, dental, and vision options available from day one in the U.S. Access to life insurance, disability coverage, and employee assistance/wellbeing support adds breadth to the health offering.
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Retirement Support — Retirement support is framed as a meaningful part of the package through plans such as a 401(k) with company matching in the U.S. These programs strengthen long-term financial security beyond base wages.
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Leave & Time Off Breadth — Time-off provisions are described as generous in some settings, including vacation availability from day one and extended holiday coverage. Flexible working arrangements and hybrid options further increase the perceived value of time-related benefits.
Airbus Insights
What We Do
Airbus is a global leader in aeronautics, space and related services. In 2020, it generated revenues of €49.9 billion and employed a workforce of around 130,000. Airbus offers the most comprehensive range of passenger airliners. Airbus is also a European leader providing tanker, combat, transport and mission aircraft, as well as one of the world’s leading space companies. In helicopters, Airbus provides the most efficient civil and military rotorcraft solutions worldwide. Airbus is an international pioneer in the aerospace industry and a leader in designing, manufacturing and delivering aerospace products, services and solutions to customers on a global scale. We believe that it’s not just what we make, but how we make it that counts; promoting responsible, sustainable and inclusive business practices and acting with integrity. Our people work with passion and determination to make the world a more connected, safer and smarter place, on the ground, in the sky and in space.
