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Data Analyst - Bosch Cluj
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Employer: | Bosch Romania |
Domain: |
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Job type: | full-time |
Job level: | 1 - 5 years of experience |
Location: |
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Updated at: | 13.09.2017 |
Remote work: | On-site |
You might be surprised how many different products are developed by Bosch Romania. So why not explore what we do, where we do it and how life is at Bosch?
- Solid background in statistics;
- Applied knowledge in machine learning / data mining or in physics / engineering;
- At least 3 years job experience in data mining, data analytics or as a process or quality engineer in a production environment;
- Project experience in the development of data analytics solutions for industrial applications;
- Capability to develop complex, efficient and scalable data driven solutions in a big data environment (Hadoop ecosystem);
- Applied knowledge of scripting languages (Python, R, SQL etc.) and in using of statistics and data mining software packages (IBM SPSS, SAS, KNIME);
- First experience with data visualization tools (Tableau, Shiny, etc) is an advantage;
- Ability to rapidly understand, analyze and find solutions to complex problems and present these;
- Independent and self-responsible way of working;
- Advanced English (German and other language skills are an advantage);
- Willingness to travel.
- As Data Scientist you will work in an international team and you will be responsible for the design, development and testing of analytical solutions based on large data streams in (near-) real-time for the international Bosch production facilities as part of the Industry 4.0 revolution;
- As part of the Analytics Service Center you will be responsible for identifying and describing the required data sources based on the input from the process engineers (business understanding), definition of data models, data quality, advanced data analysis, development and maintenance of data mining solution libraries, visualisation of data and analytics results, transfer of the analytics results into the business process of the worldwide Bosch network. This includes the integration of data from our suppliers and the forwarding of data to our end-customers (automotive and consumer electronics). The data sources include everything from flat text files, semi-structured logs, individual machine messages and sensor event streams to images from different optical tests;
Collaboration with domain specific specialists within international data mining and research projects;
- Through the participation to conferences and trainings, you will open new technological horizons to our team;
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