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Neura Robotics

Quality Problem Solving Expert (human)

Riederich, Baden-Wurttemberg, Germany

Location
Riederich, Baden-Wurttemberg, Germany
Work
On-site
Employment
Full-time
Level
Lead / staff
Function
Other
Pay
Not stated
Posted
6 months ago

About the role

Your mission & challenges

  • You lead and facilitate structured problem-solving processes for quality deviations, ensuring they are carried out efficiently and sustainably.
  • You conduct in-depth root cause analyses for internal quality issues and apply proven methods such as 8D, Ishikawa, 5-Why, FMEA, and Pareto analyses.
  • You carry out and facilitate risk analyses to identify potential quality risks at an early stage.
  • You coordinate interdisciplinary teams to develop lasting solutions and ensure the effective implementation of corrective and preventive actions.
  • You analyze quality metrics, identify systematic problem areas, and support production, development, and supplier management with complex quality issues.
  • Additionally, you are responsible for establishing and continuously improving standards for root cause analysis and problem solving.

What we can look forward to

  • You have completed a technical education or degree in engineering, production technology, or quality management.
  • You have several years of experience in quality management, quality improvement, or problem solving, and possess strong knowledge of structured problem-solving methods such as 8D, 5-Why, Ishikawa, or FMEA.
  • You have experience conducting risk analyses and facilitating interdisciplinary problem-solving teams.
  • Certification in Lean Six Sigma (Green Belt or Black Belt) or an equivalent qualification, such as Shainin Engineer, is required.
  • You demonstrate strong analytical skills and systemic thinking and work in a structured, solution-oriented, and pragmatic manner.
  • You are assertive, have excellent communication skills, and are fluent in both German and English.

Source

Posted by Neura Robotics on their own hiring page, jobs.ashbyhq.com. OptiTalent shows it as published, read 07 Nov 2026 00:56 UTC; the original is the reference.

View the original ad ↗

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