Industrial Engineering Internship: Reuse strategy high part usage modules

ASML is committed to sustainability, quality, and efficiency in its operations. Within ASML, reuse and quality initiatives play a key role in enabling circular economy goals while safeguarding system performance and value.

Reuse‑ and quality‑driven projects rely heavily on clear KPIs to assess value, risks, and impact. Ensuring alignment, consistency, and transparency across these KPIs is essential to effective project and portfolio steering.

By joining these initiatives, as an intern you'll actively contribute to fact‑based decision making, improved reuse effectiveness, and stronger quality insights across multiple projects.

Internship assignment: KPI analytics for reuse & quality initiatives

Your assignment

This internship focuses on supporting reuse‑ and quality‑related projects through KPI analytics and structured insight generation, with a strong emphasis on translating data into business‑relevant and decision‑ready insights. As an intern, you act as the analytics and insight backbone for multiple initiatives, ensuring that projects are data‑ready for steering discussions. The intern does not lead projects or make decisions, but enables the Project Leader to steer based on facts, value impact, and cross‑project patterns rather than spending time on data preparation.

As an intern, you will be responsible for:

1. KPI & Reporting Consistency

• Gather and align KPI data from existing BI reports (e.g. Quality KPIs, Reuse KPIs).
• Identify and flag inconsistencies in KPI definitions, timeframes, or scope.
• Maintain a harmonized KPI dataset that can be reused across projects.
• Perform basic data quality checks and trend validation.

2. Project Value Tracking (Reuse & Quality)

For each assigned project:

• Track baseline versus post‑intervention KPI performance.
• Support measurement of: Quality impact (e.g. DOA, CQN, defect trends) and reuse‑related differences (New versus Reuse).
• Maintain standardized project value summaries.

3. Decision‑Ready Analysis Preparation

• Prepare structured KPI overviews ahead of project reviews.
• Highlight deviations, risks, and notable trends.
• Support comparison of multiple scenarios or options (without proposing decisions).

4. Cross‑Project Insight & Pattern Detection

• Analyze data across multiple projects to detect recurring patterns.
• Identify repeating failure modes, KPI behavior, or reuse signals.
• Summarize insights in periodic overviews for the Project Leader.

5. Communication & Material Support

• Prepare clear figures and charts, one‑page summaries, and standardized slides for steering meetings.
• Ensure consistent messaging and visuals across reuse and KPI topics.

Expected deliverables

• Unified dashboards
• Harmonized KPI datasets
• Project value one‑pagers
• Decision‑ready dashboards or summaries
• Cross‑project insight snapshots
• Documented KPI assumptions and notes

Your profile

• Are a master’s student with a background in Data Science, Business Analytics, Industrial Engineering, or a similar discipline, preferably with a strong business and analytical orientation.
• Have strong analytical skills (Excel required; Power BI, Spotfire, or Azure analytics tools are a strong plus).
• Are able to translate data and KPIs into clear business‑relevant insights.
• Have an affinity with quality, reuse, and value‑driven decision making.
• Are structured, curious, and comfortable working with imperfect or evolving data.
• Possess good communication skills in English (verbal and written).

Other requirements you need to meet

• You are enrolled at an educational institute for the entire duration of the internship.
• You need to be located in the Netherlands to be perform your internship. In case you’re currently living/studying outside of the Netherlands, your CV/motivation letter includes the willingness to relocate.
• If you are a non-EU citizen, studying in the Netherlands, your university is willing to sign the documents relevant for doing an internship (i.e., Nuffic agreement).

This position requires access to controlled technology, as defined in the United States Export Administration Regulations (15 C.F.R. § 730, et seq.). Qualified candidates must be legally authorized to access such controlled technology prior to beginning work. Business demands may require ASML to proceed with candidates who are immediately eligible to access controlled technology.