Airbus Hiring Freshers For Data Scientist Intern Role | Market Standard

Job Description

• We are seeking a highly motivated and enthusiastic Data Scientist Intern with a strong interest in Machine Learning.
• This internship provides hands-on experience in developing, implementing, and evaluating ML models for real-world problems.
• Exposure to and basic understanding of Generative AI concepts will be considered a valuable asset.
• Work alongside experienced data scientists and engineers in a collaborative and supportive environment.

Responsibilities

• Data Exploration and Preprocessing: Assist in collecting, cleaning, and preparing data for ML tasks, including handling missing values, identifying outliers, and feature engineering.
• Machine Learning Model Development: Learn and apply ML algorithms (regression, classification, clustering) to solve business problems under guidance.
• Model Evaluation and Validation: Participate in evaluating model performance using appropriate metrics and techniques to ensure robustness.
• Experimentation and Iteration: Assist in designing and running experiments with different models and hyperparameters.
• Documentation and Communication: Document code, methodologies, and results clearly. Present findings in team meetings as required.
• Learning and Skill Development: Continuously learn new ML techniques and best practices through training, mentorship, and self-research.
• Exposure to Generative AI: Participate in discussions and assist in exploratory GenAI projects, including data preparation and exploring pre-trained models (if applicable).
• Collaboration: Work effectively with data scientists, engineers, and stakeholders to understand requirements and contribute to team goals.

Qualifications

• Currently pursuing or recently completed a Bachelor's or Master's in Computer Science, Statistics, Mathematics, Data Science, or a related field.
• Strong foundational knowledge of mathematics (linear algebra, calculus, probability) and statistics.
• Familiarity with data science programming languages, particularly Python.
• Basic understanding of ML concepts and algorithms (e.g., linear/logistic regression, decision trees, random forests, clustering).
• Experience with Python libraries like NumPy, Pandas, Scikit-learn, and Matplotlib/Seaborn is a plus.
• Strong analytical and problem-solving skills with the ability to interpret data effectively.
• Excellent written and verbal communication skills.
• Quick learner with the ability to adapt to new technologies and methodologies.
• Proactive attitude and strong desire to contribute to real-world projects.