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Data Analyst - Airbus-Related Programs
Orbital Critical Systems (Grupo CAF)
Anywhere · مکمل وقت
درخواست دینے والے پہلے فرد بنیں۔
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- تجربہ
- کوئی بھی
- تنخواہ
- EUR 60,000 – EUR 70,000 / year
- کھلنا
- 1
- پوسٹ کیا گیا
- 1 ہفتہ قبل
- کام کا موڈ
- دفتر میں
- تعلیم
- بی ٹیک
- اہلیت
- Candidates with a relevant degree and the right to work as European citizens, who meet the language requirements and can work on-site in Germany, may apply.
- دوبارہ شروع کریں۔
- درخواست دینے کی ضرورت ہے۔
جہاں آپ کام کریں گے۔
ملازمت کی تفصیل
Role Overview
Orbital Critical Systems, part of the CAF Group, develops safety-critical software for aerospace, defence, and transport. The company is hiring Data Analysts to work on-site in Germany on data-focused Airbus-related aerospace and defence initiatives.
The position is based in the Finkenwerder and Hamburg area.
What Makes This Opportunity Attractive
- Competitive annual compensation in the range of €60,000 to €70,000.
- Help with housing search and German language learning.
- Complete relocation support, including administrative assistance.
- The employer will handle the German tax return process for the first year.
- Permanent German employment contract tied to long-term projects.
- Team-building events and regular technical check-ins.
- An international, diverse, and innovation-oriented workplace.
Key Responsibilities
- Investigate and build inverse-design approaches using data-centric and machine-learning techniques to speed up advanced materials development.
- Translate performance targets into material configurations that reduce repeated optimisation work.
- Identify, design, and present research initiatives in composite materials and coating technologies that support the Central Research & Technology roadmap.
- Carry out research and development activities independently within a global, cross-border organisation.
- Work closely with universities, academic institutions, industrial collaborators, research organisations, and start-ups.
- Engage with the wider materials and surface-technology community to stay at the forefront of inverse-design methods.
Candidate Profile
- A degree in Materials Science, Physics, Mechanical Engineering, Aerospace Engineering, Data Science, or a closely related discipline.
- Hands-on experience or strong enthusiasm for data-driven modelling, machine learning, or inverse-design techniques.
- Practical knowledge of composite materials and/or coating technologies is a strong advantage.
- Ability to work with Python, perform data analysis, and use scientific computing tools.
- Advanced English proficiency at C1 level is required.
- German language knowledge is beneficial.
- Applicants must be citizens of a European country.
Additional Information
This is a full-time on-site role in Germany with permanent local employment terms and long-term project involvement.