Senior Analyst-Data Science (Machine Learning, LLM, GenAI)
American Express · Posted Oct 9
Banking, credit card, payment network, and travel services
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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 and enable intelligent operations. GSDS builds and scales production-ready servicing intelligence such as predictive and proactive servicing, personalization, next-best-action, conversational AI, agent assist, and complaint and dispute intelligence. This Senior Analyst role develops and implements Decision Science solutions using data, machine learning, experimentation, and emerging AI/GenAI techniques including Agentic AI, transformer-based recommendation approaches, and Conversational AI.
What you will do
- Develop analytical solutions, predictive models, recommendation and decisioning approaches that improve servicing experiences, personalization, colleague effectiveness, and operational outcomes.
- Explore and analyse large customer, behavioural, interaction, and operational datasets to identify opportunities, engineer features, test hypotheses, and translate findings into actionable solutions.
- Build and evaluate machine learning and GenAI solutions using appropriate modeling, experimentation, and validation techniques.
- 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.
- Design and analyze experiments and performance measurements to assess model/AI quality and business impact and identify opportunities for continuous improvement.
- Write high-quality analytical code and work with data, Technology, and platform partners to support productionization, monitoring, and ongoing enhancement of Decision Science solutions.
- Develop strong cross-functional relationships, communicate analytical findings clearly, and help translate technical results into recommendations that drive action.
- Stay current on advances in machine learning, GenAI, recommendation systems, and decision intelligence; test relevant methods and contribute 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).
- 2+ years of professional experience in Data Science, Machine Learning, Advanced Analytics, or a related quantitative field.
- Strong proficiency in Python, SQL, or similar analytical tools, with experience building machine learning models such as tree-based models, regression/classification models, clustering, or related techniques.
- Exposure to LLMs, GenAI, or modern deep-learning approaches and a strong interest in developing expertise in emerging AI capabilities.
- Strong analytical and conceptual thinking with the ability to solve unstructured and complex business problems.
- Strong written and verbal communication skills and ability to collaborate effectively with cross-functional partners.
Preferred qualifications
- Hands-on exposure to Agentic AI/agentic frameworks, transformer architectures, transformer-based recommendation systems, Conversational AI, LLM applications, embeddings, or semantic modeling.
- Experience with personalization, recommendation systems, next-best-action, optimization, experimentation, or customer decisioning problems.
- Experience processing and analyzing large-scale structured or unstructured datasets and translating models into scalable analytical solutions.
- Familiarity with model/AI evaluation, productionization, monitoring, or MLOps/LLMOps concepts.
- 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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