Senior Manager-Data Science (New York, NY)
About The Position
The Senior Manager, Data Science will lead end-to-end Decision Science work to build the next generation of servicing intelligence at American Express. The role translates customer, colleague, and operational challenges into analytical strategies, models, experiments, and scalable AI-driven solutions, partnering with business and Technology teams to move capabilities from concept through implementation and optimization. This role combines hands-on technical leadership with business problem solving. It advances 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. The Global Servicing Decision Science team is a centralized Decision Science Center of Excellence that partners across Product/Capabilities, Control Management, Strategy, Operations, Technology, and enterprise analytics and data science teams. Its work spans predictive and proactive servicing, personalization, next-best-action and journey orchestration, conversational AI, agent assist, AI-powered coaching, conduct and quality monitoring, and complaint and dispute intelligence.
Requirements
- Strong analytical and conceptual problem-solving skills, including 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 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.
Nice To Haves
- Master’s degree in a quantitative field such as Engineering, Computer Science, Mathematics, Statistics, Economics, or Finance.
- Experience with Agentic AI or 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.
Responsibilities
- 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.
- Design and guide development of AI/ML and GenAI solutions for 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.
- Provide hands-on technical direction on modeling choices, evaluation frameworks, data requirements, and solution trade-offs, ensuring analytical rigor and practical scalability.
- 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 experimentation, monitoring, and continuous-learning approaches to improve model and AI quality and business outcomes over time.
- Lead project teams and mentor data science colleagues, raising technical quality, first-principles problem solving, ownership, and commercial judgment.
- Synthesize complex analysis into clear recommendations and compelling narratives, and influence partners and senior stakeholders on priorities, solution choices, and execution.
Benefits
- Competitive base salaries
- Bonus incentives
- 6% company match on retirement savings plan
- Free financial coaching and financial well-being support
- Comprehensive medical, dental, vision, life insurance, and disability benefits
- Flexible working model with hybrid, onsite, or virtual arrangements depending on role and business need
- 20+ weeks of paid parental leave for all parents, regardless of gender, offered for pregnancy, adoption, or surrogacy
- Free access to global on-site wellness centers staffed with nurses and doctors, depending on location
- Free and confidential counseling support through the Healthy Minds program
- Career development and training opportunities
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
