Siemens Careers

Data Scientists Working Student (m/f) (92920SB)

Vienna, Austria
Information Technology

English (UK)

Job Description

If you really want to make a difference – make it with us

The Digital Factory Division offers a comprehensive portfolio of seamlessly integrated hardware, software and technology-based services in order to support manufacturing companies worldwide in enhancing the flexibility and efficiency of their manufacturing processes and reducing the time to market of their products – be it the automotive or aerospace industry, mechanical engineering or other interesting sectors.

We are looking for Data Scientists that will help us discover the information hidden in vast amounts of data and help us make smarter decisions to deliver even better products. Your primary focus will be in applying machine-learning techniques, doing statistical analysis and building high quality prediction systems integrated with our products.

You want to make the world a smarter place, you’re excited to shape the innovations of tomorrow and you have an excellent understanding of:

  • Machine learning techniques and algorithms
  • Common data science toolkits
  • Data visualizations tools
  • Statistics
  • Scripting and programming
  • Query languages

Your Profile:

  • At the moment you study at the university
  • Experience with data analytics, artificial intelligence and machine learning technologies
  • Analytic und strategic thinking
  • English and German fluent

What else do I need to know?

You want to join 351,000 of the smartest minds all working together to build a better future. We want to hear from you!

The gross annual payment for this job vacancy is at least EUR 29.890,00 (full-time). Siemens as an international company offers additional social benefits.

Depending on your current status and your future plans, we can offer you to work with us:

  • Working student contract: min. 20 hours /week.

Job ID: 92920

Organization: Digital Factory

Experience Level: Student (Not Yet Graduated)

Job Type: Part-time

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