Model deployment and integration: Oversee deploying AI models to production and integrating them with applications and data systems.
R&D and continuous learning: Stay current on AI and generative AI trends. Explore new model architectures and automation techniques. Evaluate emerging tools and promote responsible use of advanced AI methods.
Proven leadership: Experience leading software or AI/ML teams in an agile environment. Able to coordinate complex work, delegate effectively, and maintain high engineering standards.
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Possess deep knowledge of payment market products and programs from both issuer, acquirer and end-user client perspective.
Develop strategy and recommend new, differentiated features and benefits to enhance sales and optimization strategy for existing and prospective Bank partners, 3rd party partners, Fintech partners and startup community in order to drive new business and incremental growth for Mastercard's Small Business portfolio
Collaborate with multiple stakeholders across Account Teams, Marketing, Loyalty, Finance, Pricing and Interchange, Franchise, Legal and Customer Delivery, as well as 3rd party partners to support new launches and go-to-market initiatives
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Structure, negotiate, and manage complex partnership terms ensuring strong commercial outcomes and long-term strategic alignment.
Serve as the primary point of contact and trusted advisor for strategic merchants to build and nurture executive-level merchant relationships.
Support the execution of merchant-funded offers ecosystem, collaborating closely with Mastercard Offer Program lead to deliver compelling, best-in-class offers that drive acquisition, engagement, and retention for merchants.
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Track outcomes and detect drift: assess whether RAI initiatives are delivering expected value; pivot by redefining scope, changing approach, or halting/redirecting when necessary.
Engage directly with government agencies, regulators, and third‑party vendors to understand infrastructure, deployment constraints, security models, and operating environments.
Translate infrastructure realities into practical end‑to‑end AI solution architectures suited to the proposed use case and jurisdiction.
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Strong foundation in consulting – structured problem-solving, hypothesis-driven analysis, and crafting executive-ready narratives.
Deep expertise in analytics and data-driven decision-making – highly skilled in financial modeling and translating complex data into actionable insights.
Proven stakeholder management capabilities – experienced in influencing, challenging, and aligning senior leaders across diverse functions.
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Mastercard powers economies and empowers people across more than 200 countries and territories worldwide.
We are committed to building an inclusive, digital economy that benefits everyone, everywhere—by making transactions safe, simple, smart, and accessible. Through secure data, trusted networks, strong partnerships, and relentless innovation, we help individuals, financial institutions, governments, and businesses unlock their greatest potential.
Track outcomes and detect drift: assess whether RAI initiatives are delivering expected value; pivot by redefining scope, changing approach, or halting/redirecting when necessary.
Engage directly with government agencies, regulators, and third‑party vendors to understand infrastructure, deployment constraints, security models, and operating environments.
Translate infrastructure realities into practical end‑to‑end AI solution architectures suited to the proposed use case and jurisdiction.
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Provide Technical Leadership: Offer hands‑on leadership across data engineering projects. Conduct code reviews, enforce best practices, and promote clean, well‑tested code. Introduce improvements in development processes and tooling.
Cross‑Functional Collaboration: Work closely with engineers, scientists, and product stakeholders. Scope work, manage data deliverables in agile sprints, and ensure timely delivery of data components aligned with project milestones.
Extensive Data Engineering Experience: 8–12+ years in data engineering or backend engineering, including senior/lead roles. Experience designing end‑to‑end data systems, solving scale/performance challenges, integrating diverse sources, and operating pipelines in production.
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Mastercard’s Program aligned Site Reliability Engineering (SRE) teams are dedicated to delivering a seamless experience for our customers. We achieve this by maintaining every aspect of our Programs infrastructure and technology ecosystem to the highest standards, ensuring compliance with rigorous security requirements.
Within Mastercard, SRE focuses on the reliability and performance of core infrastructure, networks, and foundational services that power our applications. Our mission is to ensure these components operate with excellence, enabling applications to deliver an outstanding customer experience.
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