Analyst-Data Analytics
American Express · Posted Oct 1
Banking, credit card, payment network, and travel services
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About the role
Global Merchant & Network Services (GMNS) is the merchant and bank partner network of American Express, acquiring and maintaining relationships with merchants and banks that welcome American Express branded cards. The GMNS Product & GNPS Scaled Analytics Team provides scaled analytics and products to support key GMNS priorities, optimize investments, accelerate merchant and network activation, and enhance the value of American Express acceptance. This analyst role frames business problems, builds scalable analytical products and BI solutions, and works with large datasets using Python, SQL, Big Data platforms, Google Cloud services, and visualization tools to generate high-quality insights.
What you will do
- Frame ambiguous business problems, develop hypotheses, and translate complex analysis into clear, actionable recommendations for GMNS and network partner priorities.
- Deliver scalable analytical products, BI solutions, and insight frameworks that improve decision-making, strengthen partner performance visibility, and support strategic business outcomes.
- Apply analytics, automation, and modern data practices to simplify recurring workflows, improve speed to insight, and enable repeatable capability development.
- Work with large and complex datasets using tools such as Python, SQL, Big Data platforms, Google Cloud Services, and visualization platforms to generate reliable, high-quality insights.
- Build strong measurement, KPI, segmentation, trend, root-cause, reconciliation, and opportunity-sizing approaches that help identify drivers, risks, anomalies, and growth opportunities.
- Embed data quality, governance, documentation, and responsible AI principles into analytical products and processes to improve trust, consistency, and enterprise readiness.
- Partner with business, product, engineering, and regional stakeholders to shape use cases, recommend practical solutions, and drive adoption of data-backed decisions at scale.
- Bring enterprise-first thinking to the role, connecting analytics priorities to broader GMNS goals while balancing the needs of customers, partners, colleagues, and shareholders.
- Demonstrate ownership, sound judgment, and learning agility while independently navigating ambiguous, evolving, and cross-functional initiatives.
- Challenge the status quo constructively, identify opportunities for innovation, and recommend pragmatic improvements that can scale across products, processes, and teams.
- Build trusted relationships across business, product, engineering, and analytics teams, influencing stakeholders through clear communication, strong business storytelling, and transparent articulation of risks and trade-offs.
- Operate with integrity, attention to detail, and a commitment to responsible, well-governed analytical outcomes.
Skills used in this role
What the employer is looking for
- 1-3 years of relevant experience in analytics, data engineering, business intelligence, data science, or analytical product development.
- Hands-on experience using Python and SQL to analyze and transform complex datasets and deliver business insights.
- Practical experience with Tableau and/or Power BI for dashboarding, visualization, and business performance reporting.
- Exposure to cloud-based data platforms, CI/CD and modern data engineering practices particularly in environments using Google Cloud Platform or similar products will be preferred.
- Working familiarity with GenAI, prompt engineering, model-enabled applications, agentic workflow concepts, or AI-led analytics/product prototypes will be preferred.
- Prior experience in network business, payments, merchant services, financial services, or a related domain will be helpful.
- Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, Data Science, Engineering, or a related quantitative discipline.
- Preferred: Post-graduate qualification in Statistics, Mathematics, Economics, Computer Science, Data Science, Engineering, or Management.
- Proficiency in Python and SQL, with hands-on knowledge of Pandas, NumPy, and Streamlit.
- Working knowledge of data pipelines, data modeling, data transformation, and large-scale data handling concepts; exposure to Hive, PySpark, Big Data technologies, distributed systems, or Airflow-based workflow orchestration will be an added advantage.
- Hands-on experience with Tableau and/or Power BI, including dashboard design, visualization best practices, semantic metrics, performance optimization, and BI automation.
- Strong working knowledge of MS Office, particularly Advanced Excel and PowerPoint.
- Familiarity with Google Cloud Platform services such as BigQuery, Cloud Storage, Dataproc, Dataflow, Cloud Run, Dataplex, and Vertex AI will be preferred.
- Foundational understanding of prompt engineering, structured prompting, retrieval-augmented generation (RAG), embeddings and vector search, tool calling, agentic workflows, evaluation, guardrails, and responsible AI will be an added advantage.
- Familiarity with Git, APIs, predictive modeling, AI/ML algorithms, and analytical product prototyping will be helpful.
- Strong analytical and problem-solving skills with the ability to derive insights from complex data.
- Innovative thinker with strong problem-solving skills and ability to challenge the status quo to drive impactful change.
- Proven ability to manage multiple projects and deliver results in fast-paced environments.
Benefits and support
- Amex Flex, an enterprise working model that provides greater flexibility to colleagues, with colleagues working either onsite or in a hybrid model depending on role and business needs
About American Express
American Express Company is a globally recognized multinational financial services corporation specializing in payment cards, travel-related services, and network banking. Founded in 1850, the company provides charge and credit cards, expense management products, and merchant services to consumers, small businesses, and large corporations worldwide. It operates a proprietary payments network known for its premium customer engagement and lifestyle rewards programs.
- Industry
- Banking
- Company size
- 76800 employees
- Founded
- 1850-03-18
- Location
- New York City, New York, USA
- Funding stage
- Public Company
Leadership
Chairman and Chief Executive Officer
Chief Financial Officer
Chief Information Officer and Executive Vice President
Chief Colleague Experience Officer
Chief Marketing Officer
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