The AIM (Analytics, Investment & Marketing Enablement) team – a part of Global Commercial Service (GCS) Marketing – is the analytical engine that enables the GCS business portfolio of American Express. Accelerating growth momentum, increasing profitability, and strengthening our value proposition are key objectives for this organization. The team delivers consultative and innovative analytical solutions that power profitable business growth across GCS Marketing.

This role will contribute to the development and deployment of advanced analytics and GenAI-driven solutions that support GCS Acquisition, Personalization, Engagement, and US SME distribution efficiency. The primary focus will be building scalable, data-driven models and AI applications that drive measurable business outcomes. This includes enabling real-time targeting, next-best-action decisioning, conversational analytics, automated insights, and productivity-enhancing tools for Marketing and Sales teams.

The role requires strong hands-on technical expertise and the ability to translate business problems into analytical solutions. The individual will work closely with senior team members to prototype, validate, and productionize ML and GenAI use cases within enterprise environments.

The ideal candidate combines strong analytical rigor with solid technical execution skills and a curiosity for emerging AI technologies. This person should be comfortable building models end-to-end, conducting experimentation, and collaborating cross-functionally to deliver measurable impact.

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.

• Build and implement machine learning models to support targeting, personalization, and engagement optimization across Marketing channels.
• Contribute to next-best-action and treatment optimization frameworks using ML and GenAI approaches.
• Develop and support GenAI-powered tools (e.g., automated insights, prompt-based workflows, conversational analytics) to enhance marketing productivity and decision-making.
• Integrate new behavioral, engagement, and AI-generated signals into existing decisioning and prioritization systems.
• Design and execute experiments (A/B testing, test-control frameworks) to measure model effectiveness and business impact.
• Partner with Marketing, Sales, Product, and Technology stakeholders to gather requirements and ensure successful implementation.
• Support model monitoring, performance tracking, and continuous optimization efforts.
• Stay current with emerging ML and GenAI techniques and apply relevant innovations to business problems under guidance of senior team members.

Minimum Qualifications

• Master’s degree in a quantitative field (Computer Science, Engineering, Statistics, Mathematics, Physics, or related discipline) or equivalent practical experience.
• Hands-on experience building and deploying machine learning models in production or near-production environments.
• Strong proficiency in Python and SQL with experience working on large-scale datasets.
• Experience with ML workflows including data preparation, feature engineering, model development, validation, and monitoring.
• Exposure to GenAI use cases such as prompt engineering, retrieval-based systems (RAG), or integration of LLM outputs with structured data.
• Strong analytical and problem-solving skills with ability to structure business problems into data-driven solutions.
• Effective communication skills with ability to present findings clearly to business partners.
   

Preferred Qualifications

• Experience working with modern ML/LLM frameworks (e.g., PyTorch, HuggingFace, LangChain, etc.).
• Familiarity with experimentation frameworks, causal inference, or uplift modeling.
• Experience in marketing analytics, personalization systems, or decisioning platforms.
• Exposure to model deployment pipelines, MLOps practices, or cloud-based ML environments.
• Demonstrated ability to manage individual workstreams with accountability and timely delivery.