Consulting Director, Ai Strategy

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

Consulting Director, AI Strategy

Position Overview
Reporting to the Principal and working closely with the Mastercard AI team, the Senior Managing Consultant, AI Strategy will spearhead AI-driven consulting engagements for clients—especially card issuers and other financial services organizations. You will lead multidisciplinary teams of data scientists, ML engineers, and business strategists to develop long term strategies to build AI solutions and implement AI solutions that transform how clients approach analytics, automation, and value generation.
In this role, you will:
1. Shape and deliver AI strategies that address complex business challenges for payments-centric companies.
2. Advance the firm’s AI capabilities through consistent thought leadership, external outreach, and the development of new service offerings.
3. Mentor and grow junior colleagues, fostering a collaborative team culture around innovative AI methodologies.
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Key Responsibilities
1. Develop AI-Driven Strategies for Business Impact
- Identify high-impact opportunities for AI and analytics within client organizations, particularly in card issuing and payments.
- Quantify the full value potential of AI solutions, detailing the value levers, critical dependencies, and feasibility pathways to maximize ROI.
- Architect end-to-end AI solutions by combining expertise in data engineering, solution design, and domain-specific knowledge (e.g., credit card issuing).
- Secure Alignment from executive stakeholders, translating ambitious AI visions into actionable plans with clear timelines, deliverables, and success metrics.
- Scale effective AI initiatives across multiple use cases, proactively addressing technical or organizational hurdles to ensure widespread adoption.

2. Lead Rapid, Iterative AI Delivery
- Partner with AI and ML engineering leaders to oversee project roadmaps, ensuring iterative versioning, pilot rollouts, and timely stakeholder updates.
- Collaborate closely with business leaders to co-own solutions, gather continuous feedback, and adjust scopes for maximum business value.
- Drive a balanced approach to problem-solving, focusing on both technical feasibility and strategic payoff—avoiding unnecessary complexity.
- Augment client teams by providing change management and AI expertise, ensuring full realization of value and adoption of best practices.

3. Expand Thought Leadership & External Network
- Publish and present on cutting-edge AI methods and industry insights—e.g., through whitepapers, case studies, conference keynotes, and journal articles.
- Build an external network of AI experts, industry leaders, and academic partners to keep the firm at the forefront of emerging AI trends.
- Advise on best practices around AI ethics, governance, and regulatory considerations in financial services.
- Elevate the firm’s reputation by participating in relevant forums, client discussions, and industry events, driving new business opportunities.

4. Innovate & Scale the AI Operating Model
- Develop new delivery frameworks and methodologies to enhance the speed and consistency of AI project execution.
- Codify best practices, creating reusable assets (templates, playbooks) that help internal teams replicate successful approaches.
- Mentor junior colleagues, providing technical guidance and career development support to foster a robust, forward-thinking AI community.
- Champion cross-functional collaboration, ensuring alignment among data science, engineering, and business teams to deliver holistic solutions.
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Qualifications & Skills
- Experience: 8+ years leading data-driven strategies and delivering measurable outcomes (preferably in financial services, payments, or card issuing).
- GenAI Hands-on experience: Developed and deployed GenAI use cases with proven value from end to end.Developed tools with open source LLM models (e.g., Deepseek, Liama).
- Thought Leadership: Demonstrated history of publishing, speaking at conferences, or driving innovative AI solutions in a recognized industry setting.
- Communication: Excellent executive-level presentation skills and the ability to translate complex AI concepts for non-technical stakeholders.
- Agile Mindset: Familiarity with agile methodologies, iterative development, and modern technology project management practices.
- Financial Services Domain: Deep understanding of the payments ecosystem and key operational challeng