Data Scientist - Air Systems
Airbus Group India Pvt LtdJob Description
Data Scientist - Air Systems
Job Description:
Role:
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.
- 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.
Technical Skills:
Key Skills
❖ 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)
Soft Skills
● Teamwork and excellent communication skills
● Willingness to learn new skills, self-development and Problem-solving orientation
● Capability to manage conflicts and negotiation Skills
● Manage Stakeholder’s requirements and deliver high-quality results on-time
Qualification: Masters or Bachelors degree in Aerospace/Mechanical/Applied Math or related streams.
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 emsom@airbus.com.
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.
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