Data Science Engineering Summer Internship

Job Description

Airbus Commercial Aircraft seeks Summer Interns for its Data Science team in Atlanta, focusing on transforming aviation data into actionable insights.

Your Role

Key responsibilities include:
• Writing code to transform real-world data into high-signal models.
• Loading disparate data sets and conducting pre-processing transformation services.
• Extracting insights from airline and aviation data to influence business strategy and communicating these insights to partners.
• Collaborating with software development teams.
• Maintaining production systems.
• Assisting with data resource management.

About You

The company is looking for candidates who meet the following requirements:
• Currently enrolled in an accredited Bachelor’s degree program in engineering, data, or computer science.
• Previous experience as a big data engineer or relevant coursework.
• Experience with programming languages such as Python, R, Java, or similar.
• Knowledge of Data Science.
• Good project management and communication skills.
• Ability to adapt to a dynamic work environment by revising approaches based on new information.
• Eligible for employment in the US without current or future need for sponsorship.
• Effective verbal and written communication skills in English.
• Interpersonal skills to interface with all levels of personnel and disciplines.
• Strong computer skills, including MS Excel and Google Suite applications.

Preferred qualifications:
• Prior experience with Apache Spark.
• Experience with Palantir big data platform or similar platforms, or relevant coursework.
• Big data engineering coursework.

How to Apply

Submit your CV or application to consent to Airbus using and storing your information for monitoring purposes related to your application or future employment. A full job description will be provided to candidates progressing to the interview stage or upon request.

This job may close before the stated closing date, you are encouraged to apply as soon as possible

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