Senior Analyst-Data Science (Gen AI, SQL, Python)

The Analytics (AIM) team – a part of Global Strategy & Operations, GCS – is the analytical engine that enables the Global Commercial Card business. The team drives profitable growth in Acquisitions through Data, Analytics, AI powered Targeting & Personalization Capabilities.

This role will be an integral part of the customer cross-functional team responsible for driving strategic analysis and initiatives spanning across channels and products for US market. The incumbent would be responsible for analytics solutions that would shape customer acquisitions and organic growth roadmap. The role requires a strong background in data analytics and commercial card knowledge. The position is part of a highly collaborative environment, interacting with and influencing partners across the Global Commercial Service’s business at American Express.

Key Responsibilities Include:

• Support Data Driven Strategy: Conduct analysis to evaluate marketing and sales performance, identify customer trends, and uncover opportunities for growth, leveraging AI/GenAI where relevant to accelerate and enhance analytics.

• Deliver actionable insights: Translate complex data into clear recommendations for senior leadership and functional partners, supporting decision-making on customer engagement, product performance, and revenue outcomes

• Enable cross-functional decision-making: Effectively engage and deliver results in collaboration with key partners including the functional channel owners, the business partners and end-users of analytical solutions and technology partners

• Influence and storytelling: Communicate insights in a compelling way, shaping strategic narratives that drive alignment among cross-functional stakeholders and senior leaders

• Champion Innovation: Experiment with and apply emerging GenAI capabilities to solve business problems and develop innovative Amex use cases

Minimum Qualifications

• 2+ years of experience with minimum Bachelor's degree in a quantitative field (e.g. Statistics, Engineering, Physics, Mathematics and Economics).