Analyst - Data Governance & Management

Credit and Fraud Risk Credit and Fraud Risk (CFR) is a global function responsible for making effective credit and fraud risk decisions that uphold operational excellence, enable sustainable growth, and accelerate innovation across American Express. CFR brings together advanced technology, data, and analytical capabilities to strengthen risk decision-making, enable real-time customer communications, and support fraud servicing. The team plays an important role in protecting our customers and the company while enabling responsible business growth. About the Role We are looking for a Analyst – Data Governance & Management to support the development, and execution of data capabilities that support customer management risk models for the U.S. market like CDSS and TSR. In this role, you will help ensure that high-quality, reliable, and accessible data is available to support model development, performance monitoring, and ongoing analytical needs. You will work at the intersection of data, analytics, risk management, collaborating with cross-functional teams to improve how data is managed, governed, and consumed. A key focus of the role will be driving innovation in the data ecosystem. You will have opportunities to leverage technologies such as GenAI, BigQuery and Python, along with automation, to simplify data access, reduce manual effort, improve scalability, and develop more efficient and cost-effective data solutions. Develop a strong understanding of the American Express business and the key data and analytical drivers behind customer and risk management decisions. Develop, review, and maintain data capabilities supporting customer management and risk models, including datasets used for model development, execution, and ongoing performance monitoring. Analyze large and complex datasets to identify meaningful patterns, trends, data quality issues, and opportunities for improvement. Identify opportunities to automate manual processes, simplify existing workflows, and improve operational efficiency. Explore innovative approaches across data, analytics, automation, and machine learning to continuously improve existing capabilities and reduce unnecessary storage, processing, and maintenance costs. Partner with cross-functional teams across risk, decision science, analytics, technology, and other business areas to improve data accessibility, quality, governance, and usability. Structure and clearly communicate analytical findings, recommendations, risks, and business impact to leadership and key stakeholders. Navigate complex and unstructured problems by asking thoughtful questions, evaluating different approaches, and translating findings into actionable solutions. Bachelor or Master's degree in Economics, Statistics, Computer Science, Data Science, or a related quantitative field. 0–30 months of relevant experience in analytics, data management, data governance, or related data capabilities. Working knowledge of BigQuery and Python, with the ability to analyze and work with large datasets. Understanding of data analysis concepts and the ability to translate data into meaningful business insights. Ability to manage project deliverables and drive initiatives toward measurable business outcomes. Strong analytical and problem-solving skills, with the ability to work through complex and unstructured problems. Ability to quickly learn new technologies, business concepts, and data environments. Ability to work independently and take ownership of assigned deliverables while contributing effectively within a team environment. Strong written and verbal communication skills, with the ability to clearly communicate findings to both technical and non-technical stakeholders. Ability to collaborate effectively with cross-functional business partners and global teams.