Manager - Data Science

Role overview

You will join a dynamic AI and machine learning team that works across business and product groups such as credit, fraud, risk, web, mobile, marketing, and enterprise automation. The goal is to build connected solutions that expand the company’s strategic AI capabilities.

This position sits within American Express Technology, under the Enterprise Services Decision Science Center of Excellence.

What you will do

• Use AI, machine learning, and technology expertise to create scalable solutions for business problems spanning generative AI, personalization, image recognition, speech recognition, natural language processing, best next action, and time-series prediction.
• Take solutions from problem discovery and data collection through model development, validation, and delivery of production-ready systems at scale.
• Review current academic research and experiment with emerging ideas that may unlock new business value or improve existing solutions.
• Design and define deployment approaches for production-grade AI systems running on cloud infrastructure at scale.
• Lead both strategic and detailed technical design work, including design reviews when needed.
• Ensure strong code quality across the portfolio, with responsibility for innovation, functional testing, and CI/CD integration.
• Mentor junior team members and support their technical growth.
• Contribute actively to business and technical conversations and forums across the organization.

Requirements

• Master’s degree in Computer Science, Computer Engineering, Information Systems, or another STEM discipline; a PhD is preferred.
• A strong record of research output, including journal and/or conference publications, is required.
• At least 2 years of full-lifecycle product development and engineering leadership in highly available, scalable, and high-throughput systems.
• At least 2 years of experience building and delivering advanced AI or machine learning solutions that can scale effectively.
• Deep expertise in at least one area such as generative AI, machine learning, deep learning, reinforcement learning, natural language processing, optimization, probabilistic inference, information retrieval, recommendation systems, Bayesian inference, or advanced time-series forecasting.
• Practical experience with most of the listed open-source tools across orchestration, containers, model serving, observability, development environments, machine learning libraries, feature stores, and model formats.
• Ability to explain complex technical ideas clearly in written and spoken form to people at all levels of the organization.
• Strong project management skills and the ability to manage several priorities in a fast-moving environment.
• Experience with GCP and/or AWS is considered an advantage.
• Employment is subject to successful completion of a background verification check, in line with applicable laws and regulations.

About American Express

American Express is driven by a 175-year legacy of innovation, shared values, and leadership behaviors, with a long-standing commitment to supporting customers, communities, and colleagues. The company focuses on delivering differentiated products, strong customer service, and a disciplined risk mindset to uphold trust, security, and service.

As part of Team Amex, you can expect strong backing for your overall well-being, opportunities to learn, lead, and grow, and a culture where your ideas are valued and your work has real impact.

Benefits

• Competitive base pay
• Bonus incentives
• Support for financial wellness and retirement planning
• Medical, dental, vision, life, and disability coverage, depending on location
• Flexible working arrangements, including hybrid, onsite, or virtual setups based on role and business needs
• Paid parental leave, depending on location
• Complimentary access to on-site wellness centers with nurses and doctors, depending on location
• Confidential counseling support through the Healthy Minds program
• Career development and training opportunities

Additional information

The final offer is contingent on the successful completion of a background verification process, subject to relevant laws and regulations.