Summer Analytics Intern - Las Vegas
2026 Summer Data Analyst Intern
North Las Vegas, NV Fulfillment Center - Tapestry Fulfillment Center
Hourly Rate: $20/hr
Hours: 40 hours per week
Timeline: May 18th – August 7th (12 week Internship)
Major: Computer Science, Information Technology, Supply Chain or relevant
Academic Progression: Junior, Senior or Recent Graduate
**No relocation or housing assistance available**
About our Team: Our Data team, based in Tapestry’s Las Vegas Fulfillment Center, plays a critical role in driving operational excellence through data. We focus on order management, reporting, and analytics to support our operations and customer service teams. By leveraging automation, advanced analytics, and continuous improvement initiatives, we streamline processes and enhance efficiency across the fulfillment center.
We act as a bridge between operations and strategic decision-making, delivering both short-term solutions and long-term process improvements. Our work ensures accurate, timely insights that empower teams to make informed decisions, optimize order flow, and improve customer experience. Collaboration is at the heart of what we do—we partner with cross-functional teams to align data strategies with business objectives.
We are passionate about using data to solve complex challenges and create scalable solutions that drive success for Tapestry and its customers.
Internship Responsibilities:
Perform comprehensive data analyses to identify opportunities for optimization and improvement within supply chain operations. Collaborate with cross-functional teams to understand business requirements and provide data-driven solutions to address operational challenges.
Design and implement interactive dashboards and data visualization tools to effectively communicate critical operational Key Performance Indicators (KPIs).
Collaborate closely with cross-functional teams, including operations, supply chain, and business stakeholders, to understand their data needs and priorities.
Leverage data-driven techniques, such as process mining and process mapping, to gain comprehensive insights into existing processes. Conduct in-depth analyses of current operational processes and workflows to identify inefficiencies, bottlenecks, and areas for improvement.