At American Express, we empower early career data and analytics colleagues to learn, innovate, and make an impact from day one. As an Analyst Data Analytics colleague in Enterprise Technology Services, you will join a full time graduate program and 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.
- 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.
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.
- Students must have a graduation date between December 2026 and June 2027.
- 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
- 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.
Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions.