Data Analyst / Data Scientist

Role Description This full-time hybrid role is based in The Randstad, Netherlands, with a mix of on-site work at ULTRA-FLOW facilities and some work-from-home flexibility. The Data Analyst / Data Scientist will collect, clean, and analyze manufacturing, metrology, and controller data to support product quality, process optimization, and business decision-making. Daily activities include building and maintaining datasets, performing statistical analysis, developing data models, and creating dashboards and reports for stakeholders. The role collaborates closely with engineering, production, and quality assurance teams to identify trends, diagnose issues, and propose data-driven improvements. The Data Analyst / Data Scientist will also help design and implement data pipelines and contribute to continuous improvement of analytics tools and methods across the organization.QualificationsCandidates should possess strong Analytical Skills and proven experience in Data Analytics to interpret complex datasets and generate actionable insights.Candidates should possess solid knowledge of Statistics and practical experience applying statistical methods to manufacturing, quality, or operational data.Candidates should possess expertise in Data Modeling and familiarity with database structures, data warehousing, or modeling tools.Candidates should possess effective Communication skills to present findings clearly to technical and non-technical stakeholders and collaborate across teams.Relevant skills such as proficiency in Python or R, SQL, and data visualization tools (e.g., Power BI, Tableau) are highly beneficial.A bachelor’s or master’s degree in Data Science, Statistics, Engineering, Computer Science, or a related field is preferred.Experience in manufacturing, industrial automation, or metrology environments and familiarity with quality assurance processes are advantageous.Ability to work in a hybrid setting, manage multiple projects, and maintain a detail-oriented, problem-solving mindset is essential.