Data Science Intern for Airframe Structures

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 structures 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 Companys success reputation and sustainable growth.

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