Airbus Fresher Jobs 2025 | Intern - Data Scientist | Apply Now!!

Airbus has invited applications for the recruitment of Intern – Data Scientist post. It is an entry level position and freshers can apply.

Interested candidates meeting the eligibility criteria can apply online at the earliest.

Candidates can find the links for the job notification, applying online, eligibility criteria and other details here.

Airbus Fresher Jobs 2025 Details:

Experience: Freshers

Post Name: Intern – Data Scientist

Qualification: Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field

Batch: Currently pursuing or recently completed

Salary: Rs. 30k – 40k per month (expected)

Last Date to apply: As soon as possible

Job Locations: Bangalore

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Job Description:

We are seeking a highly motivated and enthusiastic Data Scientist Intern with a strong interest in Machine Learning to join our growing team. This internship offers an excellent opportunity for a student or recent graduate with limited professional experience to gain hands-on experience in developing, implementing, and evaluating machine learning models for real-world problems. While the primary focus will be on core ML techniques, exposure to and a basic understanding of Generative AI concepts will be considered a valuable asset. You will work alongside experienced data scientists and engineers, contributing to impactful projects and expanding your skills in a supportive and collaborative environment.

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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.

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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.

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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).

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How to Apply?

Interested candidates meeting the eligibility criteria have to apply at the following link: