Data Scientist

Responsibilities

• Translate complex business needs into statistical, machine learning, or AI problem spaces.
• Collaborate with IT, Data Analysts, and Data Engineers to extract data and design scalable pipelines.
• Apply scientific methods and state-of-the-art algorithms to develop solutions for aerospace challenges.
• Design and execute controlled experiments to validate optimal solutions.
• Implement industrial-grade AI solutions following software engineering best practices.
• Create monitoring protocols to ensure models align with evolving business needs and ethical AI principles.
• Communicate complex model outputs and "the story behind the data" to non-technical global stakeholders.

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 track record of leading technical projects.
• Advanced knowledge of modern architectures, including CNNs and Transformers.
• Proficiency in Python and deep familiarity with PyTorch, TensorFlow, and Scikit-learn.
• Expert knowledge of SQL and database systems (PostgreSQL, MySQL, Oracle).
• Experience with GenAI toolkits such as Hugging Face, LangChain, and LlamaIndex.
• Practical knowledge of containerization and cloud or on-premise deployment.

Preferred Qualifications

• Master's or Ph.D. in a quantitative field such as Physics, Mathematics, or Computer Science.
• Hands-on experience with Physics-Informed Neural Networks (PINNs) and hybrid modeling.
• Subject matter expertise in aviation datasets, including flight data and maintenance records.
• Experience working within a Quality Management System (QMS) to ensure reproducible and audit-ready research.

About the Company

Airbus India Private Limited is a leader in sustainable aerospace. The Airbus India Innovation Centre (AIC) focuses on digital transformation, applying advanced analytics, machine learning, and deep tech to solve critical aerospace challenges ranging from predictive maintenance to autonomous systems.