Senior Director, Head of Data & Analytics Delivery, VCA-X
Visa · Posted Nov 4
Digital payment technology platform and global payment card services corporation
IN - Bengaluru, IndiaFull-timeOnsiteDirector/Executive15+ years₹90.0L–₹1.5Cr yearly29 applicants
BankingPaymentsFinancial ServicesCredit CardsFintechPublic Company
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About the role
Visa Consulting and Analytics (VCA) is the consulting arm of Visa, solving strategic problems for issuers, acquirers, merchants, fintechs, payment enablers and governments using consulting, data analytics, technology, payments and economics expertise. VCA-X is VCA's global delivery capability, scaling high-value solutions across regions through multidisciplinary teams, common delivery standards and AI-enabled assets. This role leads the Data & Analytics Delivery pillar of VCA-X, building the people, operating model, reusable assets, standards and delivery mechanisms to deploy Data Science, Business Analytics, Data Engineering and AI-enabled analytics expertise into engagement teams.
What you will do
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
Skills used in this role
Benefits and support
- Compensation and benefits are detailed in the job posting
About Visa
Visa Inc. is a multinational payment card services corporation that facilitates electronic funds transfers worldwide. The company empowers global commerce through its secure digital payment network, connecting consumers, merchants, financial institutions, and government entities across more than 200 countries and territories.
- Industry
- Banking
- Company size
- 34100 employees
- Founded
- 1958-09-18
- Location
- San Francisco, California, USA
- Funding stage
- Public Company
Funding
Public Company · $17.9B raised
Bank of AmericaInstitutional Investors
- 2008-03-19IPO$17.9B
Leadership
RM
Ryan McInerney
Chief Executive Officer
CS
Chris Suh
Chief Financial Officer
JF
Jack Forestell
Chief Product and Strategy Officer
OJ
Oliver Jenkyn
Group President, Global Markets
KM
Kelly Mahon Tullier
Vice Chair, Chief People and Corporate Affairs Officer
Recent coverage
Visa News
Visa Fiscal Fourth Quarter and Full-Year 2026 Financial Results2026-10-27