Data Scientist and Digitalization Engineer

Airbus Group India Pvt Ltd; Bengaluru; On-site; INR 1,400,000 - 2,100,000; Full time

Job summary

Airbus India Private Limited is seeking a Data Scientist/Digitalization Engineer to lead the digital evolution of System Standard Parts and to integrate AI into qualification processes.

You will work across Design, Certification, and Manufacturing with unstructured data, developing NLP/LLM solutions, evaluating models, and visualizing insights for engineering stakeholders. The role offers exposure to aerospace analytics and professional training.

Qualifications

• DoE experience and statistical software proficiency.
• Proven ML deployment in engineering/manufacturing contexts.
• Strong Python and JavaScript scripting.
• Ability to collaborate with design, certification and manufacturing teams.

Responsibilities

• Develop Generative AI and NLP solutions using LLMs for engineering tasks.
• Conduct model evaluation to ensure performance and reliability.
• Create visualizations and demos for stakeholders.
• Craft prompts to maximize quality of outputs for technical use cases.
• Support upskilling and knowledge-sharing across the team.
• Maintain knowledge databases aligned with KM goals and engage with external partners.

Skills

Python programming

JavaScript/Apps Script

Communication skills

Cross-functional collaboration

Data visualization

Education

Bachelor's or Master's in Computer Science

Tools

JMP

Minitab

Python (SciPy, scikit-learn)

TensorFlow/PyTorch

Google AppSheet

Google Cloud/Workspace

Job description

Data Scientist/Digitalization Engineer – System Standard Parts (m/f/d) Job Description: At Airbus, our goal is to "pioneer sustainable aviation for a safe and united world". To achieve this, the System Standard Parts team is accelerating the digital transformation of our engineering cycle. We are looking for a Digitalization Engineer to lead the digital evolution of our System Standard Parts qualification processes. You will be the bridge between the current qualification processes , WoW and the digital world. You will deeply integrate Artificial Intelligence into our daily Ways of Working, focusing on key strategic pillars: optimizing design processes through advanced modeling, accelerating task execution via intelligent knowledge assistants, and enhancing V&V efficiency to ensure 'right first time' outcomes.

What we offer:

• A diverse and international team cross collaborating and supported by an agile and open-minded management team.
• Work at the intersection of engineering and advanced analytics in an aerospace environment.
• A dynamic and fast-paced business environment where your experience, expertise and knowledge directly impacts day-to-day business operations.
• 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

Responsibilities

The candidate will drive the application of data science across the domain, focusing heavily on leveraging unstructured data (technical reports, specifications, and documentation).

• Generative AI & NLP Solutions: Develop and implement innovative solutions using Large Language Models (LLMs) for critical engineering tasks, including document classification, automated text analysis, and efficient information retrieval from vast technical libraries.
• Model Evaluation & Assurance: Conduct thorough evaluations and statistical analysis of LLMs and other machine learning models to ensure they meet high standards of performance, reliability, and relevance to engineering requirements (Responsible AI).
• Insight Generation & Visualization: Create rapid, impactful visualizations and demos to effectively communicate complex data findings and model outputs to engineering stakeholders.
• Prompt Engineering & Workflow: Skillfully craft and refine prompts to maximize the effectiveness and quality of LLM outputs for technical use cases.
• Upskilling Strategy: Champion continuous professional growth by leveraging the learning ecosystems. Actively participate in the communities to exchange best practices, share knowledge, and foster a culture of collective upskilling in alignment with the broader departmental and Airbus digital strategy.
• Knowledge Management - Support team to create/manage Knowledge database and align with Airbus KM goals.
• Stakeholder Engagement: Work closely with cross-functional teams (e.g., Design, Certification, Manufacturing) and business stakeholders to understand project requirements and provide analytical support.

Who We Are Looking For

• Preferably , p ossess a Bachelor's or Master's degree in Computer Science
• 5-8 years of professional experience in digitalization or engineering data science.
• Experience in Design of Experiments (DoE) and statistical software (e.g., JMP, Minitab, or Python-based libraries).
• Proven track record in developing and deploying Machine Learning models in a physical engineering or manufacturing context.
• Proficiency in Python (SciPy, Scikit-learn, TensorFlow/PyTorch) and JavaScript/Apps Script.
• Capability in building enterprise-level solutions with Google AppSheet and managing Google Cloud/Workspace integrations.
• You demonstrate networking skills to collaborate with universities, research centers and external partners.
• Strong communication skills .
• Candidates who demonstrate prior exposure in Electrical / Mechanical / Aerospace Systems Engineering will have an added advantage.

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

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 [e-mail] .

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.