Manager, AI & Data Strategy - Technical Product Manager / Solution Engineer for Responsible AI (RAI)

Our Purpose Mastercard powers economies and empowers people in 200 countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Manager, AI & Data Strategy - Technical Product Manager / Solution Engineer for Responsible AI (RAI) Overview The AI Governance Program at Mastercard is seeking a Manager of AI System Review to advance our strategy of responsible and innovative AI deployment through rigorous risk management and effective problem-solving. This individual contributor role is part of the AI Governance operations team, focusing on comprehensive reviews of AI systems—including those developed internally and third-party solutions—across the organization. Responsibilities include conducting upfront risk assessments, verifying controls for fully developed systems, and ensuring ongoing lifecycle governance and reporting. The position is critical to enhancing productivity, automating processes, and securing Mastercard’s network. Role Summary The Manager, AI System Review, is a hands-on technical expert responsible for performing thorough assessments of all AI systems used at Mastercard. This includes reviewing risk profiles, evaluating regulatory compliance, and validating system controls throughout the AI lifecycle. The ideal candidate brings deep experience with AI and model governance, regulatory frameworks, and technical proficiency in data analytics. Key Responsibilities - Maintain and enhance robust processes for AI system reviews, including risk assessment, controls verification, lifecycle governance, and reporting. - Conduct assessments for all AI systems, both internally developed and third-party, to ensure compliance with regulatory and organizational policy and standards. - Collaborate with cross-functional teams to identify, evaluate, and mitigate AI-related risks, even when risks are not immediately apparent. - Utilize technical skills in SQL, data visualization, and statistical analyses to analyze AI systems and produce actionable insights. - Monitor and report on ongoing AI system performance, risk status, and control effectiveness throughout the system lifecycle. - Stay current with evolving regulatory requirements and ensure AI systems meet applicable compliance standards. - Provide subject matter expertise in mathematics, statistics, and regulatory frameworks as they relate to AI governance. Required Qualifications - 8+ years of experience in AI/model development and/or review, risk assessment, data analytics, or related fields. - Master’s degree or higher in mathematics, data science, engineering, physical sciences or related discipline. - Advanced knowledge of mathematics and statistics and related analyses. - Advanced knowledge of modeling methodologies, generative AI, and MLOps. - Strong understanding of standards and regulatory frameworks, and their applicability to regulated products, such as NIST AI RMF, EU AI Act, OECD, and AIA. - Proficiency in SQL and data visualization (e.g., Power BI), and programming macros, R, Python or related techniques. - Demonstrated ability to identify and address risks, including those that may not be immediately apparent, as well as the ability communicate those risks with key stakeholders in various roles. - Excellent communication, organization, and collaboration skills, both written - and verbal. Preferred Qualifications - Experience with cloud-based AI platforms (e.g., Azure, AWS, Google Cloud) and deploying scalable AI solutions. - Professional certifications in AI governance, risk management, or data privacy (e.g., Certified Information Systems Auditor, Certified AI Pr ... (truncated, view full listing at source)