Analyst, AI Center of Excellence; COE

Company Description

Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid.

At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters — to you, to your community, and to the world.

Progress starts with you.

At Visa, AI is central to our vision for the future of payments and commerce. We are committed to building enterprise-scale, responsible AI solutions that deliver measurable value for our clients, partners, and the global economy. The AI Center of Excellence (AI COE), part of the Global Data Office, is at the forefront of this mission—developing reusable AI/ML frameworks, enabling agentic AI workflows, and accelerating innovation across Visa’s data science community.

The AI COE operates as both an enterprise capability builder and an AI SWAT team, tackling high-impact projects that address complex business challenges and create scalable, reusable solutions. From evaluating cutting-edge AI methods to deploying reusable frameworks in production, our mission is to improve efficiency, adoption, and business outcomes across Visa’s global Data & AI ecosystem.

We are seeking an AI COE Analyst to contribute to technically complex AI initiatives—from research and prototyping through deployment—while advancing reusable AI capabilities and accelerating adoption across Visa.

Responsibilities:

The AI COE Analyst will:

• Design, develop, and deploy advanced AI/ML methods and agentic AI workflows that address high-value challenges across Visa.
• Contribute to the creation of reusable AI frameworks, components, and internal open-source assets for enterprise-wide adoption.
• Evaluate emerging AI/ML techniques, benchmark performance, and validate business impact using real Visa datasets and use cases.

Support the end-to-end delivery of AI COE projects, including:

• Identifying and refining problem statements with stakeholders
• Prototyping advanced models, pipelines, and automation workflows
• Building high-quality, reusable code assets
• Ensuring production readiness and integration with enterprise systems
• Develop technical documentation, metadata, and best practices for validated AI methods.
• Contribute to quality assurance through code reviews, prompt engineering support, model evaluation frameworks, and benchmark design.
• Ensure compliance with governance, security, and Responsible AI standards in all AI COE outputs.
• Quantify and communicate impact using KPIs such as model accuracy, workflow efficiency gains, adoption metrics, and business value delivered.
• Collaborate with data scientists, ML engineers, product teams, and global partners to embed AI COE solutions into enterprise workflows and maximize adoption.
• Stay current on the latest AI frameworks, agentic AI patterns, and LLM ecosystems, rapidly evaluating and prototyping new methods for potential enterprise use.

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

This role is not able to support any form of sponsorship now or in the future. (This includes support such as : J-1, F-1, CPT, or OPT and employment-based sponsorship such as: H-1B, H-1B1,E-3, O-1, TN and any EAD card holders that may need assistance in the future.)

Basic Qualifications:

• 2 or more years of work experience with a Bachelor’s Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD)

Preferred Qualifications:

• 3 or more years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD)
• 2+ years of hands‑on experience in AI/ML, data science, workflow automation, or applied machine learning research.
• Advanced degree in Computer Science, Data Science, Statistics, Business Analytics, Engineering, or a related quantitative field.
• Demonstrated experience delivering AI/ML models or agentic AI…