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Paid Internship
Work Mode
Time Spent
Required Degree
Duration

24Open Positions

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    Hilti Austria
    Schaan, Liechtenstein
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    Found 1 month ago
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    Severn Trent
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    Found 1 month ago
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Intern – Quality Management - Technical Analysis Data Scientist (m/f/x)

Hilti Austria
Found 3 weeks ago
Location
Schaan, Liechtenstein
Duration (Months)
6 Months
Time
Not disclosed
Work Mode
Not disclosed
Salary
Not disclosed
Visa Help
Only EU/EEA
Last Verified
3 weeks ago

Education

  • Master
  • PhD

Skills & Qualifications

Technical Skills

  • data science
  • AI application
  • data merging

Soft Skills

  • Technical affinity
  • Good communication skill in English.

Job Description

Quality by design. Excellence by habit. Join our team in Corporate Quality Department developing AI methods to continuously improve our products and services. You will be working on new data analysis approaches and collaborate with the global quality experts and cross functional teams. You will have the opportunity to broaden your knowledge and implement applications in practice. Start date is flexible to the student's availability, duration for at least 6 months. What You'll do As intern in our department you’ll be part of the global Hilti quality management team. Continuously controlling and improvements of product quality are the main tasks of the Corporate Quality Department. In the last time data availability from different sources increases significantly. This allows to develop analysis concepts and methods to the next level. Depending on your interests and experience, you will develop and evaluate comprehensive repair analyses combining repair and market data or develop an approach to continuously monitoring product reliability.

Requirements

  • Master student in mechanical or electrical engineering, data science, mathematics or similar
  • Good knowledge of data science and prior experience in AI application
  • Technical affinity
  • Experience in data merging
  • Good communication skill in English.

Related Field

  • AI & Machine Learning

Related Subfield

  • Applied Machine Learning

Languages

  • English
▶Apply Now

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