Computer-Stellen für Process Expert

Your Profile BS in Engineering, or similar technical discipline.Two (2) years related experience in a manufacturing environment, preferably in the field of optics.Ability to interpret technical drawings and specifications.Working knowledge of GD&T and how to evaluate.Hands on experience with manual measurement tools (calipers, micrometers, indicators, etc.) and electronic measurement equipment (vision systems, optical microscopes, comparators, etc.).Experience in product and process audits.Experience in following / maintaining an ISO 9001, 13485, AS9100 Quality Management System.Strong analytical ability and a disciplined problem-solving approach. Computer proficiency and experience using Microsoft Office software.Must be able to read, write, and speak English.Effective communication skills: listening, writing, speaking and oral presentations.

Maintain and troubleshoot data integration pipelines to ensure stable data flow into AI and analytics systems Support model development by assisting with training, validation, and optimization of machine learning workflows Conduct data analysis to extract insights and provide clear reports supporting R&D research questions Solve technical challenges related to data access, pipeline performance, and software limitations Ensure continuity of ongoing projects by aligning closely with the core team and delivering on timelines Perform image analysis and prepare datasets required for scientific and ML use cases Manage and improve ETL processes to ensure data quality, structure, and availability Document workflows, pipeline changes, and analytical steps to ensure clarity and reproducibility Academic background in computer science, data science, engineering, or a related quantitative field Strong proficiency in Python with expertise in scientific and analytical libraries Skilled in SQL and working with relational databases Understanding of ETL concepts and practical experience working with data pipelines Solid foundation in machine learning principles and model lifecycle Ability to perform image analysis for scientific or research applications Strong communication and interpersonal skills with the ability to collaborate in a technical team Independent, structured problem-solver with a commitment to clear documentation and FAIR data practices Opportunity to contribute directly to active R&D projects with immediate real-world impact Hands-on involvement in AI, machine learning, and data integration challenges in a scientific environment Close collaboration with a small, highly skilled technical team Ihr Kontakt Referenznummer 863771/1 Kontakt aufnehmen Telefon:+41 44 225 50 00 E-Mail: positionen@hays.ch Anstellungsart Freiberuflich für ein Projekt

Maintain and troubleshoot data integration pipelines to ensure stable data flow into AI and analytics systemsSupport model development by assisting with training, validation, and optimization of machine learning workflowsConduct data analysis to extract insights and provide clear reports supporting R&D research questionsSolve technical challenges related to data access, pipeline performance, and software limitationsEnsure continuity of ongoing projects by aligning closely with the core team and delivering on timelinesPerform image analysis and prepare datasets required for scientific and ML use casesManage and improve ETL processes to ensure data quality, structure, and availabilityDocument workflows, pipeline changes, and analytical steps to ensure clarity and reproducibility Academic background in computer science, data science, engineering, or a related quantitative fieldStrong proficiency in Python with expertise in scientific and analytical librariesSkilled in SQL and working with relational databasesUnderstanding of ETL concepts and practical experience working with data pipelinesSolid foundation in machine learning principles and model lifecycleAbility to perform image analysis for scientific or research applicationsStrong communication and interpersonal skills with the ability to collaborate in a technical teamIndependent, structured problem-solver with a commitment to clear documentation and FAIR data practices Opportunity to contribute directly to active R&D projects with immediate real-world impactHands-on involvement in AI, machine learning, and data integration challenges in a scientific environmentClose collaboration with a small, highly skilled technical team Ihr Kontakt Referenznummer 863771/1 Kontakt aufnehmen Telefon:+41 44 225 50 00 E-Mail: positionen@hays.ch Anstellungsart Freiberuflich für ein Projekt