At Mastercard, our technology team is at the forefront of innovation, driving technological change on a global scale with creativity and determination. Our team develops high-performing, scalable solutions for some of the world's top brands, working on cutting-edge projects from cybersecurity to emerging technologies. Our work has a global impact, enhancing everyday life for billions of people. We are revolutionizing technologies that shape our world, powering economies at speed and scale to make everyday life happen. For everyone, everywhere.
Mastercard
Teams at Mastercard
Technology
Cybersecurity and Threat Intelligence
At Mastercard, our Security Solutions team is responsible for building the solutions that protect billions of transactions, identities, and interactions every single day. Our engineers, threat hunters, and data scientists design advanced systems that safeguard the global payments network, secure digital identities, and ensure that trust scales as fast as technology does. Here, you’ll work on challenges that matter — from building AI-driven fraud prevention models and threat intelligence platforms to designing zero-trust frameworks that power commerce for people and businesses around the world.
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Mastercard Consulting Team
At Mastercard, our consultants are at the forefront of strategic transformation, using data-driven insights to craft innovative solutions that redefine business operations and drive growth. Drawing from thousands of real-world engagements, our consultants leverage first-class internal data and advanced tools to guide clients across retail, financial institutions, governments, and nonprofits from ideation to execution. Our Advisors & Consulting Services (A&CS) team offers 5 specialized service areas: Strategy and Transformation, Performance Analytics, Business Experimentation, Marketing, and Program Management.
AI and Data
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. They 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
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