About Us Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid.
At Visa, you'll have the opportunity to create impact at scale - tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world.
Join Visa and do work that matters - to you, to your community, and to the world. Progress starts with you.
Job Description Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose - to uplift everyone, everywhere by being the best way to pay and be paid.
Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.
Team Summary
Visa Consulting and Analytics (VCA) is the consulting arm of Visa, and drives tangible, impactful results for clients. Drawing on our expertise in consulting, data analytics, technology, payments and economics, VCA solves the most strategic problems for our clients. VCA's core client segments include issuers, acquirers, merchants, fintechs, payment enablers and governments.
VCA-X is VCA's global delivery capability, designed to scale high-value solutions across Regions through multidisciplinary teams, common delivery standards, AI-enabled assets, and continuous learning from delivery. Working in partnership with Regional teams and Practice Areas, VCA-X enables consistent, efficient, and scalable delivery while maintaining client and market relevance.
Data & Analytics Delivery is a core pillar of the VCA-X operating model. It provides the analytical expertise, engineering foundations, reusable solutions and AI-enabled delivery capabilities required to scale delivery across Regions and use cases. Working closely with Program Management and Specialist & Consulting Delivery teams, the function helps increase delivery capacity, improve reuse, and enable more efficient and scalable delivery.
The role operates as one of three core delivery leadership pillars within VCA-X, alongside Program Management and Specialist & Consulting Delivery. It will form part of the VCA-X Leadership Team, and report directly to the Head of VCA-X.
What a Senior Director, Data & Analytics Delivery, VCA-X does at Visa:
The Senior Director & Head of Data & Analytics Delivery, VCA-X is responsible for building and leading the globally integrated data and analytics delivery organization that will enable VCA-X to scale efficiently through reuse, automation and AI-enabled delivery.
This leader will build the people, operating model, specialist capacity, reusable assets, standards, and delivery mechanisms required to deploy Data Science, Business Analytics, Data Engineering, and AI-enabled analytics expertise into multidisciplinary VCA-X teams. The role focuses on capability-building and delivery leadership designed to help VCA-X deliver more engagements, with greater consistency, quality, speed, reuse, and leverage.
The role will work in close partnership with AI Build Team (PQL), Global Practices, regional VCA leaders, markets, consulting teams and delivery hubs. It will translate market demand, Practice priorities, and PQL-enabled workflows into scalable execution capabilities, while creating structured feedback loops that improve methodologies, data foundations, reusable solutions, and AI-enabled delivery.
The successful candidate will establish a flexible global model that matches demand with the right analytical and engineering expertise, integrates specialists into broader engagement teams, increases effective delivery capacity and throughput, and enables sustainable VCA growth and stronger client outcomes.
Core responsibilities of the role include:
Build the Global Data and Analytics Delivery Organisation
- Define and execute the capability roadmap for Data Science, Data Engineering, and AI-enabled analytics delivery within VCA-X.
- Build the talent, specialist capacity, reusable assets, standards, governance, and delivery mechanisms needed to support priority set plays and evolving market demand.
- Establish a globally integrated model that can deploy data and analytics expertise across regions, workflows, and multidisciplinary delivery teams.
- Define where specialist expertise should be pooled, embedded, or flexed based on demand, complexity, and regional requirements.
Build and Operationalize the Data & Analytics Operating Model within VCA-X
- Define how Data Science, Data Engineering and AI-delivery resources are integrated into VCA-X delivery and deployed across engagements.
- Establish clear intake, technical feasibility, scoping, effort-estimation, prioritization, staffing, handoff, quality-review, and escalation processes.
- Define decision rights, accountabilities, service expectations, and interfaces between data and analytics specialists and the broader VCA-X delivery organization.
- Build mechanisms to align analytical and engineering capacity with evolving delivery demand, expertise requirements, and strategic priorities.
- Continuously refine the operating model using delivery data, stakeholder feedback, demand patterns, and lessons from live engagements.
Translate Practice, PQL, Regional, and Market Priorities into Scalable Delivery
- Partner with Global Practices to translate gold-standard methodologies and priority set plays into repeatable analytical delivery capabilities.
- Partner with PQL to operationalize approved agents, workflows, and platform capabilities within VCA-X delivery, without duplicating PQL's build mandate.
- Work with regional leaders and markets to understand demand, data realities, valid local variations, client requirements, and adoption needs.
- Convert stakeholder priorities into capability roadmaps, staffing requirements, reusable solutions, delivery standards, and implementation plans.
- Create structured feedback loops so delivery experience informs Practice methodologies, PQL enhancements, data requirements, and future capability development.
Develop Reusable Analytics and Engineering Solutions
- Standardize repeatable analytical methods, solution architectures, data patterns, measurement frameworks, validation approaches, and delivery playbooks.
- Develop and govern reusable models, code components, pipelines, prompts, accelerators, templates, feature frameworks, and quality controls.
- Distinguish the repeatable core of each solution from justified client, market, or regional customization.
- Create mechanisms for versioning, documentation, adoption, reuse measurement, and continuous improvement of shared assets.
- Partner with Practice and PQL teams to ensure reusable solutions remain aligned with approved methodologies and platform direction.
- Establish mechanisms to capture analytical, technical and implementation learnings from engagements and translate them into reusable assets, delivery standards and capability improvements.
Enable AI-Assisted Analytics Delivery
- Drive adoption of PQL-enabled and other approved AI capabilities within VCA-X analytical delivery workflows.
- Define where activities should be agent-led, agent-assisted, or specialist-led based on quality, risk, complexity, and client needs.
- Establish evaluation, validation, human-review, and correction mechanisms for AI-generated analytical outputs.
- Identify gaps encountered during delivery and channel structured evidence and improvement requirements to PQL and Practice owners.
- Develop reusable analytical solutions, AI-enabled delivery enhancements, and engagement-level innovations that improve quality, efficiency, and scalability, while maintaining alignment with Practice methodologies and PQL-owned platforms and capabilities.
Scale Delivery Capacity and Performance
- Increase effective delivery capacity by improving reuse, specialist deployment, automation, workflow design, and cross-regional load balancing.
- Improve engagement throughput and cycle time while protecting analytical quality, client relevance, and compliance.
- Define and track measures for capacity creation, utilization, throughput, reuse, leverage, delivery reliability, quality, stakeholder experience, and business impact.
- Use performance insights to identify bottlenecks, improve staffing and workflow design, and inform investment and portfolio decisions.
- Enable VCA growth by expanding the number and range of engagements that can be delivered through VCA-X and by improving the economics of delivery.
- Partner with Program Management and Specialist & Consulting Delivery leaders to integrate analytical, engineering and consulting capabilities into cohesive engagement teams.
Build and Lead a World-Class Global Team
- Recruit, develop, deploy, and retain high-calibre Data Science, Analytics Engineering, Data Engineering, and AI-delivery talent.
- Define role architecture, career paths, capability expectations, succession plans, and specialist-development pathways.
- Build leadership depth and ensure managers can balance technical quality, people development, and delivery accountability.
- Drive fluency in AI-enabled delivery, reusable solution development, consulting collaboration, payments analytics, and global ways of working.
- Create a culture of client impact, accountability, learning, inclusion, collaboration, and continuous improvement.
Why this is important to Visa
Scaling VCA-X is central to VCA's strategy for expanding delivery capacity, accelerating execution, and creating greater impact for clients globally.
Achieving this at scale requires more than additional resources. It requires a delivery model that can efficiently deploy analytical expertise, leverage reusable solutions, operationalize AI-enabled workflows, and continuously improve through learning from delivery.
This role is critical to building the data and analytics foundation that enables VCA-X to scale. The Head of Data & Analytics Delivery will increase delivery capacity through reuse, automation, and specialist deployment; accelerate the adoption of AI-enabled delivery approaches; and ensure analytical and engineering capabilities can be consistently applied across markets, use cases, and client engagements. The role will play a key part in improving delivery efficiency, strengthening analytical excellence, and enabling the next phase of VCA-X growth.
Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager.
Qualifications Basic Qualifications:
- 18+ years of relevant work experience with a Bachelor's Degree or at least 15 years of work experience with an Advanced degree (e.g. Masters, MBA)
Preferred Qualifications:
- 18 or more years of experience with a Bachelor's Degree or 15 years of experience with an Advanced Degree (e.g. Masters, MBA)
What you will need:
- Bachelor's degree in Data Science, Statistics, Mathematics, Economics, Computer Science, Engineering, Operations Research, or a related quantitative or technical discipline.
- 18+ years of experience in business analytics, data science, data engineering, AI-enabled delivery, or related fields, including significant senior leadership experience in a global, highly matrixed organization.
- Demonstrated success building and scaling multidisciplinary analytics or technology-enabled delivery capabilities across regions.
- Strong experience designing and operationalizing global operating models spanning demand management, intake, prioritization, capacity, talent deployment, delivery governance, and stakeholder interfaces.
- Proven ability to translate business, Practice, product, platform, and market priorities into scalable delivery capabilities and measurable outcomes.
- Experience developing reusable analytical solutions, delivery standards, automation, quality controls, and performance-management mechanisms.
- Strong understanding of advanced analytics, data engineering, AI-enabled workflows, analytical platforms, and production delivery practices.
- Proven ability to lead complex portfolios, allocate specialist capacity, manage delivery risk, and improve throughput, leverage, quality, and client impact
- Strong executive communication and stakeholder-management skills, with the ability to influence senior business, Practice, product, technology, risk, regional, and market leaders.
- D emonstrated people leadership, including organization design, leadership development, succession planning, capability building, and talent retention.
- What will also help:
- Master's degree or equivalent advanced qualification in a quantitative, technical, or business discipline.
- Experience in payments, banking, financial services, consulting, or another data-intensive and regulated industry.
- Experience building a globally integrated delivery capability, shared-services model, center of excellence, or specialist talent pool.
- Experience delivering analytics and AI-enabled solutions across multiple markets, regions, and client contexts.
- Familiarity with transaction-level data, payments analytics, customer and portfolio analytics, and scalable advisory solutions.
- Experience partnering with product or platform teams to operationalize approved AI workflows, analytical products, APIs, cloud platforms, and MLOps capabilities.
- Evidence of thought leadership in analytics delivery, AI-enabled professional services, reusable solutions, or global capability transformation.
- Experience building new capabilities, operating models, or delivery organizations from the ground up.
- Ability to operate effectively across cultures, organizational boundaries, and time zones.
Visa is an EEO Employer Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.
