Support a tiered investigation framework to resolve technical failures, focusing on streamlining workflows to accelerate the resolution process.
Identify root causes of multidisciplinary system failures across Hardware, Software, and Mechanics using physical engineering principles.
Conduct technical investigations into device behavior, utilizing laboratory tools and diagnostic jigs to extract and normalize forensic data.
Contribute to data strategies by processing system logs, testing activities, and production line metrics.
Develop data models and anomaly detection algorithms to identify failure trends and optimize production stability.
Map digital signals and log signatures to physical engineering events through semantic data mapping.
Assist in building data pipelines to convert raw system data into structured, analysis-ready formats.
Communicate analytical findings and forensic insights to stakeholders to drive strategic improvements.

B.Sc. in Biomedical Engineering or Computer Science with a focus on data science.
Up to 2 years of experience in R&D, failure investigations, or laboratory work (Medical Device experience is an advantage).
Experience or academic projects involving data analysis and predictive modeling in a research or production environment.
Strong analytical capabilities and a structured, root-cause-oriented mindset.
Proficiency in Python for data analysis and automation (Pandas, NumPy, Scikit-Learn).
Understanding data engineering principles and building structured data pipelines.
Ability to define algorithm requirements, inputs/outputs, and edge cases.
Knowledge of basic statistics, data visualization, and Statistical Process Control (SPC).
Strong technical writing and communication skills in English.
Full control of all MS-Office applications including Microsoft project.
Fluent English.

Data Investigation Engineer

Key skills