Internship (d/f/m) in the field of Satellite Data Engineering, Data Analyti

at  Airbus Defence and Space GmbH

JOB DESCRIPTION:

To support our teams in in the departments TESOE1 Data Engineering Friedrichshafen and TSESG2 – Configuration & Requirements Management (NREC), Airbus Defence and Space is looking for an

DURATION: 6 MONTHS

Our department provides solutions and services in the area of digitalization of the satellite engineering process. This comprises the development and deployment of Airbus DS proprietary database systems, web applications and integrated engineering solutions, as well as services such as data management, data governance and data analysis in satellite projects. We apply state-of-the-art software development techniques and address practical problems from the spacecraft engineering domain using modern AI technologies.
We are looking for a motivated, dynamic intern, eager to learn and assist the department with tasks set out by various teams, such as research, data capturing and working closely with different team members to support our clients in satellite engineering.

DESIRED SKILLS AND QUALIFICATIONS

• Enrolled full time student (d/f/m) in Aerospace Engineering with affinity for programming, or in the area of Information Technology or Computer Science with affinity for Aerospace
• Experience with Python programming for data science
• Confident handling of MS-Office
• Knowledge in web development and/or cloud technologies (e.g. AWS) is an advantage
• Knowledge of Google Apps and/or Atlassian Apps is an advantage
• Fluent language capacity in English
• Good German skills would be beneficial
• Autonomous work style
• Curious to try new things
• Willingness to learn fast
• Good team player with excellent communication skills
  Please upload the following documents: cover letter, CV, relevant transcripts, enrollment certificate.

EXPERIENCE LEVEL:

Student

You will support various data engineers and data scientists in the design and development of data engineering software products and studies in the fields of Artificial Intelligence (AI) and Machine Learning (ML) by:

• Manipulating large datasets, e.g. time-series data
• Designing and implementing algorithms and models using existing software packages (e.g. Python libraries)
• Developing new models or improving existing models using statistical and machine/deep learning techniques, such as neural networks, decision trees, clustering approaches etc.
• Visualizing results and model performance using adequate Python libraries
• Comparing the performance of AI-based approaches with classical methods and processes
• Interpreting results from AI experiments and providing recommendations based on the findings
• Documenting your findings and results
• Helping to establish best practices for data collection, preparation, analysis and modelling
• Collaborate with stakeholders to develop AI-powered tools and algorithms for automating and enhance configuration management tasks, such CIDL generation, maintenance of the Product Tree, or PLM querying and filtering.
• Assist in the implementation of Data Science methodologies in the Change Process in order to deploy data-driven decision-making.