Masterand data based maintenance analysis (d/m/w)

Airbus; Donauwörth; Vor Ort; EUR 60.000 - 80.000; Vollzeit

Zusammenfassung

A leading aerospace company in Donauwörth is seeking a Master Thesis candidate for data-based maintenance analysis. The role involves developing machine learning methodologies, analyzing operational fleet data, and collaborating with data specialists. Ideal candidates will be enrolled in business informatics or data science and possess strong German and English skills. This opportunity offers an attractive salary, flexible working hours, and professional growth in a global environment.

Leistungen

Attractive salary

Work-life balance with a 35-hour week

International networking opportunities

Exposure to modern technologies

Qualifikationen

• Initial practical experience in data analysis is desirable.

Aufgaben

• Develop machine learning methodologies for operational fleet data analysis.
• Analyze failure rates and maintain documentation of processes.
• Work with data specialists from Airbus.

Kenntnisse

Data analysis

Machine learning

Business fluent German

Business fluent English

Ausbildung

Enrolled full-time student in business informatics, data science, or similar

Jobbeschreibung

Overview

Job Description: Airbus Helicopters is looking for a Master Thesis (d/f/m) data based maintenance analysis. You are looking for a master thesis and want to get to know the work in data based maintenance analysis? Then apply now! We look forward to you supporting us as a Masterand (d/f/m)!

Location: Donauwörth

Start: As soon as possible

Duration: 6 months

Your location

At our Donauwörth site, located on the banks of the river Danube, we develop helicopters from the initial idea to the airworthy product. Watch them take off and touch down on our own on-site test airfield.

Your benefits

• Attractive salary and work-life balance with an 35-hour week (flexitime).
• International environment with the opportunity to network globally.
• Work with modern/diversified technologies.
• At Airbus, we see you as a valuable team member and you are not hired to brew coffee, instead you are in close contact with the interfaces and are part of our weekly team meetings.
• Opportunity to participate in the “Generation Airbus Community” to expand your own network.

Your tasks and responsibilities

Goal:

• Develop a machine learning-based methodology to identify findings from operational fleetdata
• Analyse failure rates and statistical behaviour of the fleet in terms of maintenance findings
• Correlate maintenance findings with customer operational profiles and environmental conditions
• Root cause failure / damage / wear analysis

Tasks:

• Review Customer Data to identify anomalies and Train Models according a pre-processed Data Set.
• Work together with Data specialists and System Design Responsible of Airbus Helicopters
• Check if MIS Data Model can be used for other systems
• Documentation of process, models, specification
• Development experience of the proof-of-concept model

Desired skills and qualifications

• Enrolled full-time student (m/f/d) in the field of business informatics, data science, or a comparable field of study.
• Initial practical experience in the field of data analysis is desirable.
• Business fluent German and English skills.

Please upload the following documents: cover letter, CV, relevant transcripts, enrolment certificate, study regulation.

Not a 100% match? No worries! Airbus supports your personal growth.

Take your career to a new level and apply online now!

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 HELICOPTERS DEUTSCHLAND GmbH

Employment Type: Final-year Thesis

Experience Level: Student

Job Family: Customer Account and Service Management

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At Airbus, we support you to work, connect and collaborate more easily and flexibly. Wherever possible, we foster flexible working arrangements to stimulate innovative thinking.