Manager-Data Science (New York, NY)
About The Position
The Global Servicing Decision Science (GSDS) team is the Decision Science engine and centralized Center of Excellence for Global Servicing. It brings together advanced analytics, data science, AI/GenAI, and decisioning to transform servicing experiences, empower colleagues, and enable intelligent operations. GSDS partners with Product/Capabilities, Control Management, Strategy, Operations, Technology, and enterprise analytics and data science teams. Its work includes 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. The team builds durable, production-ready capabilities that improve decisions through prediction, recommendation, optimization, experimentation, and learning. As a Manager, you will contribute to and increasingly own end-to-end Decision Science work to build servicing intelligence at American Express. You will translate customer, colleague, and operational challenges into analytical approaches, models, experiments, and scalable AI-driven solutions, working with business and Technology partners to take capabilities from concept through implementation and optimization. The role combines hands-on technical depth with business problem solving and work on capabilities such as Agentic AI, transformer-based recommendation systems, and Conversational AI. You will also build your ability to lead workstreams, influence partners, and connect technical solutions to measurable customer and business outcomes.
Requirements
- Bachelor’s degree in a quantitative field such as Engineering, Computer Science, Mathematics, Statistics, Economics, or Finance.
- Strong analytical and conceptual problem-solving skills, including the ability to structure and solve business problems and work through ambiguity.
- 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 AI/GenAI techniques, with a strong technical foundation in solution development, experimentation, and model/AI evaluation.
- Experience owning analytical workstreams and collaborating across cross-functional teams to move solutions from analysis and development toward implementation and measurable impact.
- Strong written and verbal communication skills, including the ability to translate technical work into clear business recommendations and collaborate effectively with stakeholders.
Nice To Haves
- 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.
- Developing commercial acumen and storytelling skills, including connecting analytical and technical choices to customer and business value.
Responsibilities
- Own defined Decision Science problems and workstreams, from problem framing and analysis through solution development, experimentation, measurement, and ongoing optimization; seek guidance on the most complex or ambiguous challenges.
- Develop analytical approaches and decisioning solutions for servicing experiences, personalization and membership value, colleague enablement, and operational excellence.
- Design and develop 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, for servicing use cases.
- Make sound modeling and evaluation choices, identify data requirements and solution trade-offs, and seek technical guidance as needed to ensure analytical rigor and practical scalability.
- Build and enhance reusable data science products and decisioning capabilities with Technology and platform teams to support productionization and measure impact.
- Apply robust experimentation, monitoring, and continuous-learning approaches to improve model/AI quality and business outcomes over time.
- Lead defined workstreams and contribute to colleagues’ development through collaboration, knowledge sharing, and technical support.
- Synthesize analysis into clear recommendations and narratives; communicate with partners and contribute to decisions on solution choices, priorities, 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 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
Manager
