Manager, AI & Data Strategy

The Manager, AI & Data Strategy is a developing subject-matter expert responsible for advancing Mastercard's AI and data strategy through research, stakeholder engagement and practical application of responsible AI principles. The role applies advanced knowledge of AI, data, analytics and governance to support strategic initiatives, influence decision-making and contribute to improvements across products, services and business processes. Working closely with business, technology, legal, compliance, privacy and risk partners, the Manager helps evaluate emerging technologies, develops strategic recommendations, contributes to responsible AI frameworks and promotes the adoption of data-driven and AI-enabled ways of working across Mastercard.

Key Responsibilities AI and Data Strategy Execution:
Contribute to the execution of Mastercard's AI and data strategy by supporting strategic initiatives, identifying improvement opportunities and helping drive outcomes aligned to organisational priorities. Research and Trend Analysis:
Conduct advanced research into emerging AI, analytics and data trends, identifying innovative opportunities, potential risks and market developments relevant to Mastercard's products, services and operations. Thought Leadership Development:
Support internal and external thought leadership activities by synthesising industry developments, emerging technologies and regulatory trends into actionable insights for business and technology leaders. Strategic Insight Generation:
Provide data-driven analysis and strategic recommendations regarding emerging AI capabilities, including future and hypothetical risks, helping leaders make informed decisions and strengthen organisational resilience. Responsible AI Framework Development:
Contribute to the development and refinement of responsible data and AI governance frameworks, assessment models, methodologies and best practices that support innovation while protecting customer trust. Governance and Risk Support:
Support the design of forward-looking governance approaches, guardrails and ethical standards that help Mastercard proactively address evolving regulatory, societal and technology-related risks. AI and Analytics Adoption:
Advise business and technology teams on integrating innovative analytics, generative AI and agentic AI approaches into products, services and operational processes while promoting responsible usage practices.

Cross-Functional Collaboration:

Partner with product, engineering, legal, compliance, privacy, security, risk and business stakeholders to embed responsible AI and data practices into operational workflows and strategic initiatives. Data and AI Literacy:
Help foster a culture of data literacy and responsible innovation by creating practical guidance, facilitating discussions and enabling teams to better understand AI opportunities, limitations and risks. Industry Engagement and External Visibility:
Contribute to industry forums, standards discussions, research initiatives, publications and knowledge-sharing activities that enhance Mastercard's reputation as a trusted and responsible AI and data leader. Knowledge Asset Development:
Develop reusable frameworks, research summaries, evaluation approaches, governance artefacts and educational materials that can be leveraged across Mastercard. Performance Measurement and Continuous Improvement:
Assess the effectiveness of governance practices, strategic initiatives and AI adoption efforts, recommending enhancements based on new evidence, industry developments and organisational needs. Mentoring and Capability Building:
Guide junior team members through coaching, work reviews and practical development opportunities, sharing best practices and helping build expertise across the AI and data strategy discipline.

• Research and analysis help identify meaningful opportunities and risks associated with emerging AI and data technologies.
• Strategic recommendations influence business decisions and contribute to responsible innovation initiatives.
• Governance frameworks and AI assessment approaches are consistently applied across projects and initiatives.
• AI and analytics capabilities are adopted responsibly and effectively across supported teams.
• Data and AI literacy improve through educational activities, frameworks and stakeholder engagement.
• Cross-functional teams successfully embed responsible AI principles into products, services and operational processes.
• Mastercard's internal and…