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Director, Data Science
American Express. Define and lead the Decision Science roadmap across Global Servicing .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in Decision Science and AI, with a strong focus on leading data science teams, driving large-scale analytics initiatives, and translating technical strategies into measurable business outcomes. Proficient in guiding solution design and fostering collaboration across cross-functional teams to optimize operational excellence.
Highest-signal resume keywords
Decision Science Roadmap DevelopmentAI/ML Technical LeadershipData Science Team ManagementCommercial StorytellingTransformational Analytics Initiatives
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data ScienceAI/MLStatistical AnalysisPredictive ModelingOptimization TechniquesRecommendation SystemsExperimentation MethodologiesAgentic AITransformer ArchitecturesConversational AI
Soft Skills
Analytical Problem-SolvingInfluencing StakeholdersClear CommunicationExecutive StorytellingStrategic Problem Solving
Tools & Technologies
Data Science ProductsDecisioning SystemsAI EngineeringModel Evaluation FrameworksObservability Tools
Industry Keywords
Quantitative AnalysisCross-Functional CollaborationOperational ExcellenceBusiness Strategy AlignmentContinuous Optimization
About the role
Key responsibilities & impact- Define and lead the Decision Science roadmap across Global Servicing
- Identify and prioritize high-impact opportunities across servicing experiences, membership value and engagement, colleague efficiency, and operational excellence
- Translate business strategy into Decision Science priorities, success measures, and investment choices
- Provide technical leadership across AI/ML, GenAI, prediction, recommendation, optimization, experimentation, and learning
- Drive evolution toward Agentic AI, multi-agent workflows, transformer-based recommenders, representation learning, and Conversational AI/LLM-based systems
- Challenge architectures, modeling choices, evaluation frameworks, and trade-offs
- Guide teams from experimentation through scalable production deployment
- Oversee reusable, production-ready data science products and decisioning systems using customer, behavioral, contextual, and operational data
- Partner with Technology, platform, and governance teams on architecture, observability, controls, model/AI quality, and lifecycle discipline
- Lead, mentor, and grow a high-performing data science team
- Build organizational capability across Applied GenAI, AI engineering and architecture, recommendation and decisioning methods, strategic problem solving, and commercial storytelling
- Influence senior stakeholders and drive prioritization, investment decisions, adoption, and execution
- Evaluate advances in AI and Decision Science and translate relevant methods into scalable capabilities and reusable best practices
- Shape the technical roadmap across Agentic AI, Conversational AI, recommendation systems, experimentation, AI engineering, architecture, governance, and continuous optimization
Requirements
What you’ll need- Bachelors degree in a quantitative field (e.g., Engineering, Computer Science, Mathematics, Statistics, Economics)
- Exceptional analytical and conceptual problem-solving ability, with experience structuring and solving complex, ambiguous business challenges using first-principles thinking
- Proven leadership experience managing and developing high-performing analytics or data science teams in a complex, cross-functional environment
- Strong technical foundation in modern data science and AI
- Ability to guide solution design, challenge technical approaches, and connect analytical choices to business outcomes
- Strong ability to influence senior stakeholders through clear, structured, and compelling communication and executive storytelling
- Experience driving large-scale analytics, Decision Science, or AI initiatives from concept through production, adoption, and ongoing optimization
- Strong commercial acumen and storytelling, with the ability to connect technical strategy, architecture and investment choices to measurable business value
- Preferred: Master’s degree in a quantitative field
- Preferred: Technical exposure to Agentic AI/agentic workflows, transformer architectures and transformer-based recommendation systems, Conversational AI, LLMs, and advanced personalization or next-best-action systems
- Preferred: Strong understanding of the end-to-end Decision Science and AI lifecycle, including experimentation, model/AI evaluation, decision logic and orchestration, productionization, monitoring, governance, and continuous optimization
- Preferred: Track record of building scalable data products, recommendation/decisioning systems, or AI-driven capabilities with measurable outcomes
- Preferred: Experience driving transformation from traditional analytics toward AI-powered, productized Decision Science capabilities and reusable enterprise solutions
Benefits
Comp & perks- Competitive base salaries
- Bonus incentives
- Support for financial well-being and retirement
- Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location)
- Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need
- Generous paid parental leave policies (depending on your location)
- Free access to global on-site wellness centers staffed with nurses and doctors (depending on location)
- Free and confidential counseling support through our Healthy Minds program
- Career development and training opportunities