Campus Undergraduate Summer Internship Program - 2027 Data Analytics, Enterprise Technology Services- Phoenix, AZ

Business Unit / Role Specific Info The Enterprise Technology Services organization partners with every part of the American Express business to power the company’s growth and innovation with trust and efficiency, and drive competitive differentiation with speed. We support the delivery and operations of technology, digital, and data capabilities, platforms, and services globally. Specifically, our team is responsible for the company’s technology engineering, architecture, and infrastructure, providing 24x7 support to ensure an uninterrupted, high-quality experience for customers and colleagues. We also provide product management for core enterprise platforms, and lead technology risk and information security, enterprise data governance and platforms, digital product and design, and enterprise AI platforms on behalf of the company. At American Express, we empower future data professionals to learn, innovate, and make an impact from day one. As a Data and Analytics Intern in Enterprise Technology Services, you will join a 10 week Summer Internship Program and support analytics work that helps technology teams make informed decisions across governance, architecture, modeling, data science, and emerging technology initiatives. This role is designed for students interested in using data, analytics, financial insight, modeling, AI, or quantitative methods to solve business and technology problems. Depending on team alignment, you may work with technology business enablement, governance, model focused teams, enterprise business data architecture, data science teams, or quantum computing exploration efforts. Potential Focus Areas American Express Data and Analytics Interns may be aligned to different technology teams based on business needs, project requirements, and individual strengths. Experience in one or more of the following areas is beneficial: • Technology Business Enablement: portfolio analysis, financial management, delivery analytics, resource insights, operating rhythm materials, executive reporting, or business performance analysis. • Actuarial, Modeling, and AI Governance Analytics: quantitative analysis, actuarial methods, model documentation, model output review, scenario analysis, model governance, AI oversight, or responsible AI concepts. • Enterprise Business Data Architecture: data requirements and data-source analysis, source-to-target mapping, metadata and lineage, data quality and controls, data governance and standards, and foundational enterprise data architecture concepts. • Data Science: Python, R, SQL, exploratory analysis, statistical analysis, predictive modeling fundamentals, evaluation metrics, feature review, visualization, or insight generation. • Quantum Computing Exploration: Quantum computing fundamentals, emerging technology research, use case evaluation, experimentation documentation, technical landscape analysis, or early stage analytics. • Core Skills Across All Areas: analytical thinking, attention to detail, communication, collaboration, intellectual curiosity, responsible use of data and AI, and ability to explain insights to technical and non technical audiences.