Quality Intelligence Dashboard Intern – Data Analytics & CS

ASML US, LP. (US30); Veldhoven; Hybrid; EUR 11,000 - 17,000; Full time

Benefits offered by this job

Job summary

ASML in the Netherlands invites a master’s internship in data analytics and computer science focused on building a unified quality intelligence dashboard. You will develop dashboards, analyze inspection and operational data, and explore automation and AI-enabled improvements with a global stakeholder group.

You will work 4+ days per week, with at least 3 days on-site, gaining hands-on experience in analytics, quality management, process improvement, and stakeholder engagement.

Qualifications

• Pursuing a master's degree in a data analytics, computer science, operations management, systems engineering, process engineering, or related field.
• Experience with dashboard development, data analytics, or BI projects is preferred.
• Ability to translate data into actionable insights and collaborate with international stakeholders.
• Familiarity with Python, Power BI, AI-enabled analytics tools or similar data science technologies.

Responsibilities

• Design and develop a consolidated dashboard for quality and inspection reporting
• Visualize inspection volume flows across warehouses and customer locations
• Build scenario analysis capabilities to evaluate quality and cost impacts
• Analyze inspection and operational data to identify improvement opportunities
• Generate insights that support preventive quality actions and process improvements
• Explore AI-enabled and automation opportunities within quality management processes
• Collaborate with stakeholders to translate business needs into data-driven solutions

Skills

Dashboard dev

Data analytics

Python

Power BI

AI analytics

Education

Master's degree (MS/MSc)

Tools

Power BI

Job description

ASML in the Netherlands invites a master’s internship in data analytics and computer science focused on building a unified quality intelligence dashboard. You will develop dashboards, analyze inspection and operational data, and explore automation and AI-enabled improvements with a global stakeholder group.

You will work 4+ days per week, with at least 3 days on-site, gaining hands-on experience in analytics, quality management, process improvement, and stakeholder engagement.