Analyst-Data Analytics

The Global Merchant & Network Services (GMNS) organization is responsible for managing relationships with millions of Merchants and Partners around the world that facilitate American Express acceptance and enabling the day-to-day operations of our company s payment network. The newly created U.S. Merchant Marketing, Global Marketing Execution & Analytics (UMGEA) team is responsible for leveraging marketing and analytics capabilities to drive sustainable growth through customer, partner, and product insights that inform the merchant value proposition, channel strategy, and investment optimization, while leveraging the full range of enterprise assets and partnerships for GMNS customers and ensuring we remain compliant as a network. The GMNS Analytics team within UMGEA is responsible for partnering with global markets to drive profitable growth, accelerating acceptance and amplifying the value of Amex acceptance to Merchants, bank partners and Card Members at scale. We offer powerful data and actionable insights to attract new businesses to engage with Amex, help existing businesses improve performance and capitalize on new opportunities.

The GMNS Analytics team is seeking an Analyst to support the Merchant Portfolio Reporting & Insights, Global Marketing Execution & Analytics function. This role will design, enhance, and scale global analytics, reporting and dashboards that provide clear visibility into merchant and cardmember trends, outcomes, and performance drivers. The Analyst will partner closely with marketing teams of global markets, and data engineering to build dashboards and conduct bespoke analysis to deliver timely, accurate, and actionable insights that strengthen merchant network and cardmember vibrancy. The role will also contribute to modernization initiatives, leveraging automation, scalable data solutions, and emerging capabilities such as GenAI and machine learning.

• 1+ years of relevant experience in analytics, business intelligence, reporting, or a related analytical domain.
• Strong intellectual curiosity and attention to detail, with the ability to learn quickly, solve problems, and deliver results.
• Ability to derive actionable insights from data, manage multiple priorities, and deliver high-quality outcomes in a fast-paced environment.
• Strong collaboration and stakeholder-management skills, with the ability to build effective relationships and constructively challenge the status quo.
• Excellent written and verbal communication skills, with the ability to synthesize complex information, present insights clearly, and influence stakeholders at different levels.
• Experience in the merchant, payments, financial services, or related industry is preferred.

• Working knowledge of SQL, Google BigQuery, Tableau, Advanced Excel, and PowerPoint.

• Experience with data analysis, reporting, visualization, and dashboard development.

• Exposure to machine learning, cloud technologies, GenAI, or analytics automation is a plus.

Academic Background:

• Bachelor s degree in Statistics, Mathematics, Economics, Engineering, Data Science, or a related quantitative discipline.
• Postgraduate degree in Statistics, Mathematics, Economics, Engineering, Management, Data Science, or a related discipline is a plus.

• Own and manage global strategy analytics, reporting and dashboards, ensuring timely updates, data accuracy, consistency, and robust quality-control processes across markets.
• Conduct deep-dive analytics across merchant and Card Member data, including trend analysis, anomaly detection, and root-cause analysis, to provide end-to-end visibility into business trends, outcomes, and operational KPIs across markets.
• Analyze performance across global, regional, market, and product dimensions to identify key performance drivers, emerging risks, underlying root causes, and opportunities to improve operational efficiency and business outcomes.
• Deliver bespoke merchant, Card Member, and portfolio-level analyses to identify actionable opportunities and support high-ROI marketing and business strategies.
• Support GenAI and machine-learning proof-of-concept initiatives, evaluating emerging technologies and analytical approaches to modernize analytics products, improve scalability and automation, and address evolving reporting and analytics requirements.
• Translate complex analytical findings into actionable business insights, enabling stakeholders to make data-driven decisions and prioritize opportunities across markets and portfolios.
• Drive continuous improvement of reporting and analytical products by identifying opportunities to automate recurring processes, strengthen data-quality controls, and enhance the usability and scalability of dashboards and insights.