Job Description:

Job description: Data Science Intern for Airframe Structures

Team: Structures – Aerostructures Data Management

Background:  

Enable advanced digital capabilities in the perimeter of Airframe related Design, Modeling, Simulation, Testing and Inspection along the lifecycle of Aircraft development using Data Analytics / Artificial Intelligence / Machine Learning.

Role:  

The Intern will act as a Data Scientist focusing on Airframe related applications with the task to provide safe and balanced  data driven design solutions. They will play a key role in developing machine learning and deep learning (classification, regression, time-series and natural language processing including Generative AI) models and/or analytics dashboards & stand-alone web applications to analyze aircraft structure’s operational reliability and build  predictive and prescriptive models that assist in modeling, simulation and automation. They need to engage in tasks related to data engineering, knowledge graph creation, chatbot building, tuning and monitoring.

Technical Skills 

Key Skills  

• Programming Proficiency: Foundational knowledge and hands-on experience in Python. Familiarity with basic data manipulation libraries like Pandas and statistical packages.

• Machine Learning (ML) Basics: Basic understanding of supervised learning concepts (Classification, Regression), and exposure to Deep Learning (DL) or Neural Networks is a plus.

• NLP & Generative AI Curiosity: Strong interest in Natural Language Processing (NLP) and Large Language Models (LLMs). Project experience involving text analysis or LLMs is highly desirable.

• RAG System Exposure: Demonstrated understanding or project experience with Retrieval-Augmented Generation (RAG) architecture, vector databases, and advanced context-based querying.

• Model Evaluation: Basic statistical knowledge for analyzing model performance and reliability.

• Visualization: Ability to create simple yet clear dashboards or demonstrations using tools like Streamlit, Dash, or similar environments (e.g., academic projects in Palantir/Skywise).

• Data Driven Thinking: Demonstrated ability to approach a problem by asking concrete analytical questions and seeking data-based insights.

• Cloud & Deployment Awareness: Basic familiarity with cloud concepts (AWS, Azure, or GCP) and the principles of deploying code (MLOps).

• Prompt Engineering: Understanding of how to structure inputs (Prompt Engineering) to get the best results from AI tools.

Good to have (not mandatory)  

❖ Basic understanding of System Engineering and Aerospace/ Aviation

❖ Basic knowledge on model distillation of LLMs

❖ Basic Knowledge on finetuning & performance optimization of LLMs

❖ Exposure to Software testing; Verification, Validation & Uncertainty Quantification of ML

Preferred Language: Python

Data Science Frameworks: Scikit-Learn, Keras, Tensorflow, Pytorch, Langchain etc.  

Environments: Jupyter Notebook / Anaconda, Visual Studio etc.

Soft Skills:  

● Teamwork and excellent communication skills  

● Willingness to learn new skills, self-development and Problem-solving orientation  

● Fail-fast mindset and Solutions approach

Qualification: Pursuing (final year) or completed Masters or Bachelors degree in Aerospace, Mechanical, Thermal or Data Science related streams.

Job Location: Bangalore 

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.

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