Data Scientist Algorithm/ML Engineering Metrology (m/f/d)

High technology and innovation...

…actively shaping and driving forward – for this position, we are looking for a dedicated personality (m/f/d) who convinces with ingenuity, responsibility, and technical competence. As a consulting firm, we support our clients in finding a suitable person who understands challenges not as hurdles, but as exciting opportunities for further development.

What awaits you:

• Development and industrialization of algorithms and machine learning for the evaluation of optical measurement data

• Setup and further development of data science platforms for demanding applications in metrology

• Conception and implementation of modular evaluation software as well as reusable analysis components

• Transfer of prototypes and feasibility studies into robust, testable, and maintainable software solutions

• Analysis of complex measurement data for data-based optimization of measurement methods, models, and system performance

• Validation and optimization of algorithms and software directly on optical measurement systems

• Interdisciplinary collaboration with specialist departments from optics, metrology, software, and system development

Certain technical and personal prerequisites are helpful for this position. The following requirements give you an overview of the experiences and qualities that are advantageous for this role.

What you should bring:

• University degree in Data Science, Computer Science, Physics, Mathematics, Engineering, or a comparable field

• Sound programming and software development experience, preferably with Python

• Practical experience in machine learning, data science, or algorithm engineering

• Experience in transferring analytical approaches into robust and maintainable software solutions

• Physical understanding, ideally in optics, metrology, signal processing, or image processing

• Systematic problem-solving, interdisciplinary collaboration, and understandable communication of complex technical contexts

• Hands-on experience in testing and further development of algorithms on real measurement systems

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