American Express—Senior Analyst/Analyst- Data Analytics

Job description

Description: The UMGEA – Global Analytics team is seeking an Analyst for the Field Analytics team. The Analyst will support the build and rollout of scalable merchant intelligence capabilities that help identify actionable opportunities, enable retention and growth initiatives, and inform Client Management and Marketing treatments across GMNS. This role will support work across merchant triggers, retention analytics, trigger arbitration, treatment playbooks, and predictive insights. The Analyst will help translate analytical opportunities into clear business actions, supporting the transition of insights and pilots into governed, production-ready capabilities through platforms. The role requires strong analytical problem-solving, attention to detail, execution discipline, and the ability to turn complex data into practical recommendations that can be activated by field, Client Management, and Marketing partners. Requirements: - 2-4 years of relevant experience in analytical domain. - Intellectual curiosity, attention to detail ability to learn quickly and drive results. - Ability to drive insights from data, manage multiple projects and drive results in a fast-paced environment. - Strong collaboration skills with ability to build relationships and challenge the status quo. - Excellent business writing and presentation skills with the ability to communicate effectively, build relationships and influence at all levels. - Technical Skills: Familiarity with Google Big Query, SQL, Python, Lumi, PySpark and Tableau. - Experience in dispute analytics, risk operations, or merchant business preferred. - Experience in Machine Learning/ Cloud / Gen AI is a plus. Academic Background: - Bachelors in Statistics/Mathematics/Economics/ Engineering/Data Science with relevant experience. - Post Graduation in Statistics/Mathematics/ Economics/Engineering/Management is a plus. Responsibilities: - Provide analytic and execution support for merchant retention, trigger arbitration, treatment playbooks, and predictive insights that enable GMNS growth initiatives and CLM priorities. - Analyze merchant performance, spend, engagement, coverage, and behavioral trends to identify early indicators of decline, retention risk, and growth opportunities and support field activation decisions. - Support the development and scaling of merchant trigger capabilities, including deterministic and predictive triggers that help enable timely, insight-led interventions. - Help translate analytical pilots and proof-of-concepts into governed, production-ready capabilities through enterprise platforms such as TargetIQ. - Partner with cross-functional stakeholders to understand business questions, define analytical requirements, and deliver timely, high-quality insights. - Translate complex data into clear, concise findings, treatment recommendations, and business actions that can be understood and acted upon by partners. - Support automation and standardization of recurring analytics processes to improve efficiency, reduce operational risk, and increase speed to market.