Responsibilities:

• Data Exploration and Preprocessing: Assist in collecting, cleaning, and preparing data for machine learning tasks. This includes handling missing values, identifying outliers, and performing feature engineering.
• Machine Learning Model Development: Learn and apply various machine learning algorithms (e.g., regression, classification, clustering) to solve specific business problems under the guidance of senior team members.
• Model Evaluation and Validation: Participate in evaluating model performance using appropriate metrics and validation techniques to ensure robustness and generalization.
• Experimentation and Iteration: Assist in designing and executing experiments to test different models and hyperparameter configurations.
• Documentation and Communication: Document code, methodologies, and results clearly and concisely. Participate in team meetings and present findings as required.
• Learning and Skill Development: Actively learn new machine learning techniques, tools, and best practices through training materials, mentorship, and independent research.
• Exposure to Generative AI (Good to Know): Participate in discussions and potentially assist with exploratory projects related to Generative AI, such as understanding basic concepts, exploring pre-trained models, or assisting with data preparation for GenAI tasks (if applicable).
• Collaboration: Work effectively with data scientists, engineers, and other stakeholders to understand project requirements and contribute to team goals.

Qualifications:

• Currently pursuing or recently completed a Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.  

• Strong foundational knowledge of mathematics (linear algebra, calculus, probability) and statistics.
• Familiarity with programming languages commonly used in data science, particularly Python.
• Basic understanding of core Machine Learning concepts and algorithms (e.g., linear regression, logistic regression, decision trees, random forests, k-means clustering).
• Experience with relevant Python libraries such as NumPy, Pandas, Scikit-learn, and Matplotlib/Seaborn is a plus.
• Strong analytical and problem-solving skills with the ability to interpret data and draw meaningful conclusions.
• Excellent communication (both written and verbal) and interpersonal skills.
• Ability to learn quickly and adapt to new technologies and methodologies.
• A proactive attitude and a strong desire to learn and contribute to real-world projects.

Good to Know:

• Basic understanding of Generative AI concepts and models (e.g., Large Language Models (LLMs), diffusion models).
• Familiarity with any deep learning frameworks (e.g., TensorFlow, PyTorch).
• Experience with version control systems (e.g., Git).
• Exposure to cloud computing platforms (e.g., AWS, GCP).

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:

Internship

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Experience Level:

Student