Director-Data Science
American Express · Posted Oct 8
Banking, credit card, payment network, and travel services
Gurugram, HR, IndiaFull-timeHybridDirector/Executive12+ years₹90.0L–₹1.5Cr yearly93 applicants
BankingPaymentsCredit CardsFinancial ServicesPublic Company
Full time
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About the role
The Global Servicing Decision Science (GSDS) team is the Decision Science engine for Global Servicing at American Express, bringing together advanced analytics, data science, AI/GenAI, and decisioning to transform servicing experiences, empower colleagues, and enable intelligent operations. GSDS builds and scales servicing intelligence spanning predictive and proactive servicing, personalization, next-best-action and journey orchestration, conversational AI, agent assist, AI-powered coaching, and complaint and dispute intelligence. This Director role defines and leads the vision, strategy, and execution of Decision Science across Global Servicing, leading a team of data science professionals and advancing capabilities such as Agentic AI, transformer-based recommendation systems, and Conversational AI.
What you will do
- As Director, you will define and lead the vision, strategy, and execution of Decision Science across Global Servicing, translating complex customer and business challenges into scalable intelligence capabilities that improve customer experience, colleague effectiveness, operational efficiency, membership value, and controls.
- This is a highly visible leadership role requiring deep analytical rigor, strong technical and AI expertise, strategic problem-solving, commercial acumen, and enterprise leadership. You will lead a high-performing team of data science professionals and partner across Global Servicing and the enterprise to embed intelligent decisioning into servicing experiences and processes.
- You will also help shape the next generation of servicing Decision Science—advancing capabilities such as Agentic AI, transformer-based recommendation systems, and Conversational AI while ensuring solutions are production-ready, measurable, governed, and continuously improving.
- Define and lead the Decision Science roadmap across Global Servicing, identifying and prioritizing high-impact opportunities across servicing experiences, membership value and engagement, colleague efficiency, and operational excellence.
- Translate business strategy into clear Decision Science priorities, success measures, and investment choices, connecting technical opportunities to measurable customer and business outcomes.
- Provide technical leadership across AI/ML, GenAI, prediction, recommendation, optimization, experimentation, and learning, setting a high bar for solution design, evaluation, and analytical rigor.
- Drive the evolution of GSDS toward emerging AI paradigms, including Agentic AI and multi-agent workflows, transformer-based recommenders and representation learning, and Conversational AI/LLM-based systems that can reason over context and support increasingly intelligent servicing decisions.
- Maintain sufficient technical depth to challenge architectures, modeling choices, evaluation frameworks, and trade-offs, and to guide teams from experimentation through scalable production deployment.
- Oversee development of reusable, production-ready data science products and decisioning systems that leverage customer, behavioral, contextual, and operational data to enable timely and personalized decisions.
- Partner with Technology, platform, and governance teams to deploy and evolve AI solutions with appropriate architecture, observability, controls, model/AI quality, and lifecycle discipline.
- Lead, mentor, and grow a high-performing team of data science professionals, fostering technical excellence, first-principles problem solving, innovation, ownership, and strong commercial judgment.
- Build organizational capability across Applied GenAI, AI engineering and architecture, advanced recommendation and decisioning methods, strategic problem solving, and commercial storytelling.
- Influence senior stakeholders and build strong cross-functional accountability, using clear and compelling narratives to drive prioritization, investment decisions, adoption, and execution of major Decision Science initiatives.
- Continuously evaluate advances in AI and Decision Science and translate the most relevant methods into practical, scalable capabilities and reusable best practices for Global Servicing.
- Shape a forward-looking technical roadmap that strengthens GSDS capabilities in Agentic AI, Conversational AI, modern recommendation systems, experimentation, AI engineering, architecture, governance, and continuous optimization.
Skills used in this role
Data ScienceAIMachine LearningGenAILLMsAgentic AIConversational AITransformer architecturesRecommendation systemsPersonalizationNext-best-actionExperimentationOptimizationDecision Scienceleadershipcommunicationproblem solving
What the employer is looking for
- 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, with the 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 qualifications
- Master’s degree in a quantitative field (e.g., Engineering, Computer Science, Mathematics, Statistics, Economics).
- Technical exposure to or experience driving modern AI capabilities such as Agentic AI/agentic workflows, transformer architectures and transformer-based recommendation systems, Conversational AI, LLMs, and advanced personalization or next-best-action systems.
- 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.
- Track record of building scalable data products, recommendation/decisioning systems, or AI-driven capabilities with measurable customer, revenue, productivity, cost, or control outcomes.
- Experience driving transformation from traditional analytics toward AI-powered, productized Decision Science capabilities and reusable enterprise solutions.
Benefits and support
- 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
About American Express
American Express Company is a globally recognized multinational financial services corporation specializing in payment cards, travel-related services, and network banking. Founded in 1850, the company provides charge and credit cards, expense management products, and merchant services to consumers, small businesses, and large corporations worldwide. It operates a proprietary payments network known for its premium customer engagement and lifestyle rewards programs.
- Industry
- Banking
- Company size
- 76800 employees
- Founded
- 1850-03-18
- Location
- New York City, New York, USA
- Funding stage
- Public Company
Leadership
SJ
Stephen J. Squeri
Chairman and Chief Executive Officer
CL
Christophe Le Caillec
Chief Financial Officer
RR
Ravi Radhakrishnan
Chief Information Officer and Executive Vice President
MR
Monique R. Herena
Chief Colleague Experience Officer
ER
Elizabeth Rutledge
Chief Marketing Officer
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