Internship American Express Data Entry Jobs (NOW HIRING)

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 early career data and analytics interns to learn, innovate, and make an impact from day one. As an Analyst Data Analytics intern in Enterprise Technology Services, you will support analytics work that helps technology teams understand portfolio performance, delivery progress, financial trends, resource utilization, and operational outcomes. 

This role sits at the intersection of technology, finance, portfolio management, reporting, and data analytics. You may gather and validate data, build reports, analyze financial or delivery metrics, support dashboards, develop insights, and prepare clear recommendations that help leaders and teams make informed technology decisions. 

At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. From delivering differentiated products to providing world-class customer service, we operate with a strong risk mindset, ensuring we continue to uphold our brand promise of trust, security, and service.

As part of Team Amex, you'll experience our powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express.

We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally:

• Competitive base salaries
• Flexible work arrangements and schedules with hybrid and virtual options with Amex Flex
• Free access to global on-site wellness centers staffed with nurses and doctors (depending on location)
• Free and confidential counselling support through our Healthy Minds program
• Career development and training opportunities

For a full list of Team Amex benefits, visit out Colleague Benefits Site.

The below represents the expected salary range for this job requisition. Ultimately, in determining your pay, we'll consider your location, experience, and other job-related factors.

Minimum 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.
• Coursework, 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. 

Our team reviews applications on a rolling basis. We appreciate your patience while we consider your application and will contact qualified candidates regarding next steps. 
 

Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions.
 

Ideal Candidate Profile

We are seeking curious and analytical students who enjoy working with data, solving complex problems, and learning how analytics can support responsible technology decisions. Successful candidates will combine quantitative thinking, business curiosity, strong communication skills, and a commitment to accuracy, integrity, and continuous learning.

Responsibilities and What Type of Work to Expect 

• 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.