Campus Graduate Masters Summer Internship Program - 2027 Data Analytics, Enterprise Technology Services- Palo Alto, CA

About the role

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.

Responsibilities

• Collect, clean, validate, and organize data from portfolio, project, financial, operational, and technology delivery sources to support analysis and reporting.
• Analyze portfolio performance, budget, forecast, resource, delivery, schedule, quality, and risk information to identify trends, insights, and areas for follow up.
• Create and maintain dashboards, reports, key performance indicators, recurring analytics outputs, and leadership ready summaries for technology stakeholders.
• Develop financial models, cost views, forecast summaries, scenario analyses, and variance insights that support technology portfolio and project decision making.
• Partner with technology, finance, product, project, and business teams to understand reporting needs and translate them into accurate analytical outputs.
• Support Software Development Lifecycle and Agile delivery reporting by analyzing delivery metrics, progress data, dependencies, and execution patterns.
• Prepare presentations, narratives, and stakeholder updates that communicate data-backed insights to technical and non-technical audiences.
• Use Agentic AI, reporting, data analytics, and productivity tools to support research, summarization, analysis, workflow efficiency, and human validated outputs.

Qualifications

• Must have earned a Master’s degree in Business Administration, Finance, Information Technology, Information Systems, Business Analytics, Data Analytics, Computer Science, Economics, or another relevant field before the full-time start date.
• Interest or experience in data analytics, financial management, portfolio reporting, technology delivery, business intelligence, or data-informed decision-making.
• Foundational knowledge of data analytics concepts, including data collection, validation, analysis, visualization, and insight generation.
• Foundational understanding of financial management principles such as budgeting, forecasting, cost tracking, variance analysis, or financial modeling.
• Awareness of Software Development Lifecycle and Agile methodology concepts within a technology delivery environment.
• Foundational understanding of Generative AI concepts, responsible use, appropriate use contexts, prompt-based workflows, and human validation of AI-generated outputs.
• Strong analytical thinking, attention to detail, communication, organization, problem-solving, and collaboration skills.

Preferred Qualifications

• Master’s degree candidates with an expected graduation date between December 2027 and June 2028.
• Courses, projects, internships, student organizations, or extracurricular experience related to data analytics, finance, business analysis, reporting, portfolio management, or technology delivery.
• Experience using analytical, reporting, or presentation tools such as Excel, PowerPoint, SQL, Python, Tableau, Power BI, or similar platforms.
• Exposure to financial modeling, dashboard development, key performance indicator reporting, forecast reconciliation, cost analysis, or operational analytics.
• Interest in technology portfolio management, project performance reporting, resource planning, process improvement, or business intelligence modernization.
• Familiarity with project or portfolio tools such as Jira, Rally, Confluence, SharePoint, Microsoft Project, or related workflow platforms.
• Coursework, projects, research, or internship exposure to data requirements, source-to-target mapping, data quality and controls, metadata, lineage, or data governance.
• Exposure to financial modeling, dashboard development, statistical analysis, scenario analysis, model documentation, data quality review, metadata, or data lineage concepts.
• Interest in AI governance, model risk management, responsible AI, explainability, enterprise data architecture, predictive analytics, or quantum computing research.
• Curiosity about Agentic AI reporting, AI-enabled analytics, productivity tools, automated insight generation, and responsible validation of AI-generated recommendations.
• Ability to build clear narratives from data, communicate findings clearly, and work effectively across finance, technology, architecture, risk, product, and business teams.

Benefits

We offer a competitive base salary, flexible work arrangements and schedules with hybrid and virtual options with Amex Flex, free and confidential counseling support through our Healthy Minds program, career development and training opportunities, and comprehensive support for your holistic well-being, including free access to global on-site wellness centers staffed with nurses and doctors (depending on location).

Pay

Ultimately, in determining your pay, we’ll consider your location, experience, and other job-related factors.

Schedule

Depending on role and business needs, colleagues will either work onsite, in a hybrid model (combination of in-office and virtual days) or fully virtually.