Manager - Data Science (Python, SQL, Gen AI)

The Analytics, Investments and Marketing Enablement (AIM) team within Global Commercial Services Marketing (GCSM) powers customer acquisition, engagement, and retention through data, advanced analytics, and AI.

Within AIM, the Customer Experience Optimization (CXO) Personalization – GCS Digital Acquisitions team is focused on building scalable, intelligent personalization for SME customers across acquisition channels—including website and application experiences.

This team sits at the intersection of AI/GenAI, advanced analytics, and digital product, with a mandate to build AI-native personalization capabilities. The team is responsible for shaping how we deliver relevant, context-aware experiences to SBS and Corporate prospects in real time, with a strong focus on building scalable systems and capabilities, not just analyzing outcomes.

At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. From delivering differentiated products to providing world-class customer service, we operate with a strong risk mindset, ensuring we continue to uphold our brand promise of trust, security, and service.

As part of Team Amex, you’ll experience our powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express.

In this role, you will focus on executing personalization strategies and developing analytical solutions that improve customer engagement and conversion. You will work closely with cross-functional partners to embed personalization into digital experiences and support the delivery of scalable, data-driven use cases.

CXO Personalization & Digital Experience Design

• Support the design and implementation of personalization strategies across acquisition touchpoints (website, landing pages, application flows).
• Analyze behavioral and contextual data to inform targeted messaging, content, and offers.
• Collaborate with product and engineering teams to integrate personalization into digital platforms.
• Apply machine learning and GenAI techniques to develop personalization use cases (e.g., segmentation, next-best-action).
• Contribute to building and testing models that enable improved targeting and customer experience.
• Work with large datasets to generate insights and build analytical solutions.
• Develop reusable code, models, and frameworks under guidance.
• Support deployment and monitoring of models in production environments

AI / GenAI-Driven Decisioning

Scalable Data Science & Systems Thinking

Problem Solving & Insight Generation
• Tackle ambiguous, high-impact business problems with structured, hypothesis-driven thinking.
• Synthesize data into clear, actionable insights that inform product and experience design.
• Apply measurement as a supporting tool to validate and refine personalization strategies.

• Master’s degree in a quantitative field (e.g., Engineering, Computer Science, Mathematics, Statistics, Economics).
• Exceptional analytical and problem-solving skills, with the ability to break down complex, ambiguous problems into structured solutions.
• Demonstrated ability to solve open-ended problems with minimal structure, applying strong first-principles thinking and logical rigor.
• Strong programming experience in Python, SQL, or similar languages.
• 2-3 years of hands-on experience with machine learning techniques (e.g., regression, clustering, tree-based models, or similar).
• Experience working with large-scale data and building analytical solutions in a digital or product environment.
• Demonstrated ability to work across cross-functional teams (product, engineering, marketing).
• Strong communication skills with the ability to translate complex ideas into clear, actionable narratives.

Preferred Qualifications

• Experience in personalization, recommendation systems, or real-time decisioning.
• Familiarity with digital ecosystems (e.g., web/app analytics, identity resolution, martech stacks, experimentation platforms).
• Exposure to or hands-on experience with GenAI applications (e.g., LLMs, prompt engineering, AI-assisted workflows).
• Experience building or contributing to end-to-end data products or decisioning systems.
• Strong intuition for customer experience design and digital journeys.
• Ability to operate in a fast-paced, build-oriented environment with a focus on impact and scalability.