ASML US, LLC is hiring a Supply Chain Analytics intern within its Customer Support and supply chain operations environment. The intern will analyze ticket data, identify process improvement opportunities, and develop reporting, documentation, recommendations, and a sustainable handoff for stakeholders.
Responsibilities
Analyze operational and supply chain ticket data to identify patterns, inefficiencies, root causes, and improvement opportunities
Develop clear reports, presentations, process documentation, and recommendations for technical and non-technical audiences
Collaborate with cross-functional stakeholders to validate findings and support implementation of process improvements
Document and present project findings, outcomes, and recommendations in an end-of-internship presentation
Create a repeatable process, reporting structure, and knowledge-transfer package that can be sustained after the internship
Perform ticket bucketing analysis to organize tickets into meaningful categories
Create a bucket-level breakdown explaining why tickets were created
Identify the top recurring ticket types and associated themes
Determine which ticket types are the most time-consuming and assess their operational impact
Draw conclusions from the analysis to identify opportunities for systematic process or Ways of Working (WoW) corrections
Manage stakeholder alignment and collaboration to drive process improvements
Formulate a proposal to correct identified gaps and improve operational efficiency
Present the analysis, findings, and business implications to stakeholders
Set up a sustainable reporting, documentation, and handoff process for use after the internship is complete
Create dashboards, data visualizations, and concise management-ready summaries
Write and update work instructions, process flows, standard operating procedures, lessons learned, and best-known methods
Develop clear definitions, assumptions, data dictionaries, and analytical methodologies so results can be reproduced
Assess current processes and documentation using continuous improvement principles such as Lean and root-cause analysis
Partner with stakeholders across functions to verify data quality, test conclusions, and prioritize improvement actions
Track recommendations, decisions, owners, and follow-up actions through project closeout
Qualification
Required
Currently pursuing a bachelor's degree or master's degree in Data Analytics, Data Science, Business Analytics, Business Management, Global Supply Chain Management, Operations Management, Industrial Engineering, Information Systems, or an equivalent discipline
Proficiency with Microsoft Office applications, particularly Excel, PowerPoint, Teams, OneNote, and Word
Excel and analytical tools, including the ability to organize, clean, analyze, and visualize data
Ability to use AI tools responsibly to support analysis, documentation, research, and productivity
Strong presentation development and business storytelling skills
Ability to draw clear, evidence-based conclusions and convert findings into actionable proposals
Technical writing skills, with the ability to create accurate, structured, and user-friendly documentation
Can-do attitude, curiosity, and willingness to learn
Collaboration and stakeholder management skills across technical and business teams
Ability to identify trends, bottlenecks, recurring issues, and improvement opportunities
Attention to detail and a high degree of accuracy
Ability to manage assignments independently, meet deadlines, and follow through with minimal supervision
Clear, concise, and professional written and verbal communication
Result-driven mindset with ownership and accountability
The candidate must be authorized to work in the United States without the need for employer sponsorship
Preferred
Coursework or project experience involving data analysis, business process improvement, technical writing, supply chain, or operations is preferred
Advanced Excel capabilities such as PivotTables, XLOOKUP, data validation, Power Query, and charts
Experience with Power BI, Tableau, SQL, Python, or similar analytical tools is a plus
Familiarity with process mapping, root-cause analysis, Pareto analysis, and continuous improvement methods is a plus
Ability to structure technical content for different audiences, from process users to leadership stakeholders
