Business Insider
At Mastercard, AI is helping to power fraud-detection systems
At Mastercard, our AI and Data teams set direction, build shared capabilities, and work side-by-side with cross-functional teams to scale AI and data responsibly across the organization.
Core teams within AI and Data
The problems you'll work on
Our AI and Data teams help solve challenges that cut across products, regions, and customer needs. Examples include:
Core teams within AI and Data
- AI and Data Strategy - partners closely with product teams during design and development to drive strategic use of data and AI across services and platforms.
- AI Engineering, Data Engineering, and Data Science - design, build, deploy, and operate models, pipelines, and platforms that power analytics, AI products, and services at scale.
- Data Analytics - translate complex data into insights that inform decisions, product performance, and business outcomes.
- AI and Data Governance - establish standards, policies, and oversight to ensure data and AI are high-quality, well-controlled, and used responsibly across the company.
- AI Centre of Excellence - focuses on the most critical AI and data science efforts, shared tooling, and research that enables future AI use cases
The problems you'll work on
Our AI and Data teams help solve challenges that cut across products, regions, and customer needs. Examples include:
- building AI systems that support safer, smarter, and more personal commerce
- developing shared data platforms and lakehouse capabilities to accelerate innovation
- improving data discoverability, quality, and lifecycle management
- advancing AI deployment, monitoring, and operations at enterprise scale
- supporting new AI ideas through a structured AI intake and prioritization process
Join us, and together, we'll redefine what's possible in secure, efficient transactions, protecting partners, suppliers, customers, and consumers worldwide.
