Analyst-Data Science
American Express · Posted Oct 12
Banking, credit card, payment network, and travel services
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About the role
The Global Servicing Decision Science (GSDS) team is American Express's centralized Decision Science Center of Excellence, building and scaling servicing intelligence across Global Servicing through advanced analytics, data science, AI/GenAI, and decisioning. Its mandate spans predictive and proactive servicing, personalization, next-best-action and journey orchestration, conversational AI, agent assist, and quality monitoring. As an Analyst, you will contribute to development and implementation of Decision Science solutions using data, machine learning, experimentation, and emerging AI/GenAI techniques to solve customer, colleague, and operational problems.
What you will do
- Contribute to analytical solutions, predictive models, recommendation and decisioning approaches that improve servicing experiences, personalization, colleague effectiveness, and operational outcomes.
- Explore and analyze customer, behavioral, interaction, and operational datasets to identify patterns and opportunities, engineer features, test hypotheses, and translate findings into actionable insights and solutions.
- Develop and evaluate machine learning and GenAI solutions using established modeling, experimentation, and validation techniques, with guidance as needed.
- Gain hands-on experience and contribute to emerging capabilities such as Agentic AI and agentic workflows, transformer-based recommendation systems, Conversational AI/LLM applications, and advanced personalization or next-best-action solutions.
- Support the design and analysis of experiments and performance measurements to assess model/AI quality, business impact, and opportunities for improvement.
- Write high-quality analytical code and work with data, Technology, and platform partners to support implementation, productionization, monitoring, and enhancement of Decision Science solutions.
- Build effective cross-functional relationships, communicate analytical findings clearly, and translate technical results into insights and recommendations.
- Build knowledge of advances in machine learning, GenAI, recommendation systems, and decision intelligence; test relevant methods and contribute to reusable approaches and best practices across GSDS.
Skills used in this role
What the employer is looking for
- Master’s degree in a quantitative field (e.g., Engineering, Computer Science, Mathematics, Statistics, Economics, Finance).
- Relevant academic, internship, or professional experience in Data Science, Machine Learning, Advanced Analytics, or a related quantitative field.
- Proficiency in Python, SQL, or similar analytical tools, with foundational experience building machine learning models such as tree-based models, regression/classification models, clustering, or related techniques.
- Exposure to or coursework/project experience with LLMs, GenAI, or modern deep-learning approaches, with strong interest in developing expertise in emerging AI capabilities.
- Strong analytical and conceptual thinking with the ability to structure problems, learn quickly, and work through ambiguity.
- Strong written and verbal communication skills and the ability to work effectively in collaborative, cross-functional teams.
Preferred qualifications
- Exposure through professional work, internships, research, or academic projects to Agentic AI/agentic frameworks, transformer architectures, transformer-based recommendation systems, Conversational AI, LLM applications, embeddings, or semantic modeling.
- Exposure to personalization, recommendation systems, next-best-action, optimization, experimentation, or customer decisioning problems.
- Experience or project exposure working with structured or unstructured datasets and developing analytical or machine learning solutions.
- Familiarity with model/AI evaluation and basic concepts related to productionization, monitoring, or MLOps/LLMOps.
- Curiosity about customer servicing and the ability to connect technical work to measurable customer and business outcomes.
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
Chairman and Chief Executive Officer
Chief Financial Officer
Chief Information Officer and Executive Vice President
Chief Colleague Experience Officer
Chief Marketing Officer
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