Senior Manager-Data Science

About the Team:

The Global Servicing Decision Science (GSDS) team is the Decision Science engine for Global Servicing, bringing together advanced analytics, data science, AI/GenAI, and decisioning to transform servicing experiences, empower colleagues, and enable intelligent operations. GSDS serves as a centralized Decision Science Center of Excellence, partnering across Product/Capabilities, Control Management, Strategy, Operations, Technology, and enterprise analytics and data science teams.

GSDS builds and scales servicing intelligence across Global Servicing—from predictive and proactive servicing, personalization, next-best-action and journey orchestration to conversational AI, agent assist, AI-powered coaching, conduct and quality monitoring, and complaint and dispute intelligence. Our mandate is to build durable, production-ready capabilities that continuously improve decisions through prediction, recommendation, optimization, experimentation, and learning.

How will you make an impact in this role?

As a Senior Manager, you will lead end-to-end Decision Science work that helps build the next generation of servicing intelligence at American Express. You will translate complex customer, colleague, and operational challenges into analytical strategies, models, experiments, and scalable AI-driven solutions, partnering across business and Technology teams to move capabilities from concept through implementation and optimization.

This role combines hands-on technical leadership with strong business problem solving. You will help advance modern capabilities—including Agentic AI, transformer-based recommendation systems, and Conversational AI—while guiding project teams, influencing partners, and ensuring solutions deliver measurable customer and business outcomes.

 

Decision Science & Business Problem Solving:

• Own complex Decision Science problems end to end—from problem framing and opportunity sizing through solution design, experimentation, measurement, and ongoing optimization.
• Develop analytical strategies and decisioning solutions across servicing experiences, personalization and membership value, colleague enablement, and operational excellence.

AI / GenAI & Advanced Modeling:

• Design and guide development of AI/ML and GenAI solutions spanning prediction, recommendation, optimization, experimentation, and intelligent orchestration.
• Apply and evaluate modern AI approaches—including Agentic AI and agentic workflows, transformer-based recommenders and representation learning, Conversational AI/LLM systems, and advanced personalization or next-best-action methods—to servicing use cases.
• Provide hands-on technical direction on modeling choices, evaluation frameworks, data requirements, and solution trade-offs, ensuring analytical rigor and practical scalability.

Scalable Solutions & Execution:

• Build and evolve reusable data science products and decisioning capabilities, partnering with Technology and platform teams to move solutions into production and measure their impact.
• Establish robust experimentation, monitoring, and continuous-learning approaches that improve model/AI quality and business outcomes over time.

Leadership & Cross-Functional Influence:

• Lead project teams and mentor data science colleagues, raising the bar on technical quality, first-principles problem solving, ownership, and commercial judgment.
• Synthesize complex analysis into clear recommendations and compelling narratives; influence partners and senior stakeholders on priorities, solution choices, and execution.

 

Minimum Qualifications:

• Strong analytical and conceptual problem-solving skills, with experience structuring and solving complex, ambiguous business problems.
• Strong hands-on foundation in data science and machine learning, with proficiency in Python, SQL, or similar tools and experience building and evaluating predictive or decisioning models.
• Experience applying modern AI/GenAI techniques and the technical depth to guide solution design, experimentation, and model/AI evaluation.
• Demonstrated experience leading complex analytical projects and collaborating across cross-functional teams to drive solutions from concept toward production and measurable impact.
• Strong written and verbal communication skills, with the ability to translate technical work into clear business recommendations and influence stakeholders.

Preferred Qualifications:

• Master’s degree in a quantitative field (e.g., Engineering, Computer Science, Mathematics, Statistics, Economics, Finance).
• Experience with Agentic AI/agentic workflows, transformer architectures or transformer-based recommendation systems, Conversational AI, LLMs, or related modern AI capabilities.
• Experience with personalization, recommendation systems, next-best-action, optimization, customer decisioning, or intelligent automation.
• Understanding of the end-to-end Decision Science lifecycle, including experimentation, productionization, monitoring, governance, and continuous optimization.
• Experience working with large-scale customer, behavioral, interaction, or operational datasets and developing reusable data science products.
• Strong commercial acumen and storytelling, with the ability to connect analytical and technical choices to customer and business value.

 

Depending on factors such as business unit requirements, the nature of the position, cost and applicable laws, American Express may provide visa sponsorship for certain positions.