American Express is a global financial services company operating across banking, finance, and B2B payments. Its business includes consumer, business, and corporate credit cards; payment and merchant services; savings accounts, certificates of deposit, and personal loans; as well as rewards, travel programs, corporate payment solutions, financial education, security services, and cardmember and merchant support.
Director of Data Science - American Express - New York Hybrid
Lead AI and Decision Science strategy for American Express Global Servicing, developing production-ready decisioning, recommendation, and conversational AI capabilities.
Description
- Set and direct the Decision Science roadmap for Global Servicing
- Find and rank high-value opportunities across servicing, membership engagement, colleague productivity, and operational performance
- Convert business strategy into Decision Science priorities, success metrics, and investment decisions
- Provide technical direction across AI and machine learning, generative AI, prediction, recommendation, optimization, experimentation, and learning
- Advance Agentic AI, multi-agent workflows, transformer-based recommendation, representation learning, and conversational AI or LLM systems
- Assess architectures, modeling decisions, evaluation methods, and technical trade-offs
- Move teams from experimental concepts to scalable production implementations
- Oversee reusable, production-ready data science products and decisioning systems built from customer, behavioral, contextual, and operational data
- Collaborate with Technology, platform, and governance teams on AI architecture, observability, controls, quality, and lifecycle management
- Lead, mentor, and develop a high-performing data science organization
- Expand capabilities in applied generative AI, AI engineering and architecture, advanced recommendation and decisioning, strategic problem solving, and commercial communication
- Advise senior stakeholders and lead prioritization, investment, adoption, and delivery of major Decision Science programs
- Monitor developments in AI and Decision Science and turn relevant approaches into practical, scalable capabilities and reusable practices
- Define a long-term technical roadmap spanning Agentic AI, conversational AI, modern recommendation, experimentation, AI engineering, architecture, governance, and continuous optimization
Requirements
- Bachelor’s degree in a quantitative discipline such as engineering, computer science, mathematics, statistics, or economics
- Outstanding analytical and conceptual problem-solving skills, including the ability to structure and resolve complex, ambiguous business problems using first-principles reasoning
- Demonstrated experience leading and developing high-performing analytics or data science teams in complex, cross-functional organizations
- Strong technical grounding in contemporary data science and artificial intelligence
- Ability to shape solution design, question technical approaches, and link analytical decisions to business results
- Ability to engage senior stakeholders through clear, structured communication and persuasive executive storytelling
- Experience taking large-scale analytics, Decision Science, or AI programs from conception through production, adoption, and continued optimization
- Strong commercial judgment and storytelling skills that connect technical strategy, architecture, and investment decisions to measurable value
- Preferred: Master’s degree in a quantitative discipline
- Preferred: Experience with Agentic AI, agentic workflows, transformer architectures, transformer-based recommendation, conversational AI, LLMs, advanced personalization, or next-best-action systems
- Preferred: Knowledge of the full Decision Science and AI lifecycle, including experimentation, model and AI evaluation, decision orchestration, production deployment, monitoring, governance, and ongoing optimization
- Preferred: Record of creating scalable data products, recommendation or decisioning systems, or AI capabilities with measurable results
- Preferred: Experience converting traditional analytics into AI-powered, productized Decision Science capabilities and reusable enterprise solutions
- Visa sponsorship may be available for some positions based on business unit requirements, role, cost, and applicable law
Benefits
- Competitive base salary
- Bonus opportunities
- 6% company retirement savings match
- Complimentary financial coaching and financial well-being resources
- Comprehensive medical, dental, vision, life insurance, and disability coverage
- Flexible work arrangements, including hybrid, onsite, or virtual options depending on the role and business needs
- More than 20 weeks of paid parental leave for all parents, regardless of gender, for pregnancy, adoption, or surrogacy
- Complimentary access to onsite wellness centers with nurses and doctors, subject to location
- Free confidential counseling through the Healthy Minds program
- Career development and training programs
- Equity where applicable
- Visa sponsorship may be available for some positions based on business unit requirements, role, cost, and applicable law