Jobs

Data Scientist/Digitalization Engineer – Materials & Processe
Bangalore Area
·
On-site
·
Full-time
·
2w ago
Job Description:
At Airbus, our goal is to "pioneer sustainable aviation for a safe and united world". To achieve this, the Material, Processes & Test (M&P) team is accelerating the digital transformation of our engineering cycle. We aim to move from traditional empirical testing to a data-driven "Materials 4.0" approach where data science, high-fidelity simulations, and AI converge to design our future components that are sustainable, high-performing, and digitally mastered from lab to flight.
We are looking for a Digitalization Engineer to lead the digital evolution of our material testing and qualification processes. You will be the bridge between the physical laboratory and the digital world, using AI/ML to predict material behavior, Simulation to virtually validate processes, and Google Workspace infrastructure to create agile, professional-grade tools for our global engineering community..
What we offer:
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A diverse and international team cross collaborating and supported by an agile and open-minded management team.
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Work at the intersection of physical engineering and advanced analytics in a R&D environment.
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A dynamic and fast-paced business environment where your experience, expertise and knowledge directly impacts day-to-day business operations.
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The opportunity to grow continuously in your field of expertise and develop yourself supported by professional training and a network of enthusiastic and knowledgeable colleague
Your Main Responsibilities
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Define and implement the data strategy for the M&P team, transitioning manual material characterization processes into automated, scalable digital workflows.
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Drive "future-ready" initiatives by developing ML models (Predictive Analytics, Neural Networks, etc.) to standardize and harmonize the products and standards .
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Lead simulation activities (e.g., Finite Element Analysis or multi-scale modeling) and integrate these physical models with data-driven AI approaches to create robust Digital Twins of materials and processes.
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Act as the department’s statistical lead, using Advanced DoE to optimize complex test matrices, ensuring maximum statistical confidence with minimum resource expenditure.
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End-to-end management of the M&P digital toolkit. You will lead the development, deployment, and maintenance of custom software solutions used by M&P engineers including building apps via App Sheet for field/lab data collection and using Google Apps Script to integrate disparate data sources into a unified cloud environment.
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Serve as the technical lead in international R&D projects, collaborating with universities, material suppliers, and IT departments to align digital tools with aerospace standards
Who We Are Looking For
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Master’s degree or PhD in Material/Mechanical/Aerospace Engineering or equivalent
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5-8 years of professional experience in digitalization, material informatics, or engineering data science.
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Expert in Design of Experiments (DoE) and statistical software (e.g., JMP, Minitab, or Python-based libraries).
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Proven track record in developing and deploying Machine Learning models in a physical engineering or manufacturing context.
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Proficiency in Python (Sci Py, Scikit-learn, Tensor Flow/Py Torch) and JavaScript/Apps Script.
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Experience with material/process simulation tools (e.g., LAMMPS, MedeA, Abaqus, Ansys, or similar)
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Capability in building enterprise-level solutions with Google App Sheet and managing Google Cloud/Workspace integrations.
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You demonstrate networking skills to collaborate with universities, research centers and external partners.
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Strong communication skills to translate "Data Science" into "Material Science" for diverse stakeholders..
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 Limited:
Employment Type:
Permanent
Experience Level:
Professional
Job Family:
Digital
By 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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About Airbus

Airbus
PublicAirbus SE is a European aerospace corporation. While the company's primary business is the design and manufacture of commercial aircraft, it also operates separate divisions for Defence and Space and Helicopters.
10,001+
Employees
Leiden
Headquarters
$89B
Valuation
Reviews
3.7
10 reviews
Work-life balance
3.2
Compensation
4.0
Culture
4.1
Career
3.5
Management
3.8
72%
Recommend to a friend
Pros
Learning opportunities and professional development
Supportive team and collaborative environment
Good compensation and benefits
Cons
High pressure and performance expectations
Long hours and overwhelming workload
Bureaucratic and rigid structure
Salary Ranges
42 data points
Junior/L3
L2
L3
L4
L5
L6
Junior/L3 · Data Science Engineer
1 reports
$114,826
total per year
Base
$88,327
Stock
-
Bonus
-
$114,826
$114,826
Interview experience
5 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Offer rate
20%
Experience
Positive 20%
Neutral 80%
Negative 0%
Interview process
1
Application Review
2
HR Screen
3
Hiring Manager Interview
4
Technical Assessment
5
Final Interview
6
Offer
Common questions
Technical Knowledge
Behavioral/STAR
Past Experience
Culture Fit
Problem Solving
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