Analyst- Risk Management

Description

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 companys payment network. The people, processes, and technology that support this vital function are evolving to improve the merchant experience and economics. Within GMNS, the Global Strategy, Operations & Performance (GSOP) teams mission is to deliver a best-in-class premium merchant member experience that will get merchant to not only accept American Express but openly welcome and recommend us to their customers.

Responsibilities

• Drive analytical and control-focused initiatives from problem definition through execution and monitoring
• Assess data, processes, and controls to identify gaps, inconsistencies, and risk areas
• Perform root cause analysis on issues and partner with stakeholders to implement practical solutions
• Develop and track key metrics (KRIs/KPIs) to monitor performance, data health, and process effectiveness
• Analyze datasets to generate insights, identify trends, and support data-driven decision making
• Support design and implementation of controls and monitoring frameworks to improve accuracy and reliability
• Collaborate with cross-functional teams (Business, Risk, Compliance, Data) to align priorities and drive outcomes
• Support investigations, escalations, and remediation tracking related to data, process, or control gaps
• Contribute to process improvements with a focus on scalability, efficiency, and automation
• Participate in governance, reporting, and ongoing improvement initiatives

Qualifications

• Graduate/Postgraduate in a quantitative or business field
• 3+ years of experience in Data Quality, Data Analysis, Risk, or related domains
• Certifications in Data Analytics, Risk, or Process Excellence are a plus

Key Skills

• Strong analytical and logical thinking with a structured problem-solving approach
• Ability to quickly understand data flows, identify gaps, and drive practical solutions
• Experience working with data tools (e.g., SQL, Excel, Power BI); Python or automation skills are a strong plus
• Understanding of data quality dimensions (accuracy, completeness, consistency, timeliness)
• Ability to build and scale data quality checks, controls, and monitoring frameworks
• Strong ownership mindset with ability to operate independently in ambiguous environments
• Effective stakeholder management and clear communication of data issues and impact
• Continuous improvement mindset with focus on efficiency, automation, and scalability