# Director, Data Analytics at Mastercard

AI Level 1, AI centrality 20 out of 100. O'Fallon, Missouri.

## Details

- Company: [Mastercard](https://jobsbylevel.com/companies/mastercard)
- AI level: AI Level 1 (score 20 out of 100)
- Location: O'Fallon, Missouri
- Posted: October 6, 2026
- Apply: https://jobsbylevel.com/go/cef888f7-68d9-4ebd-b197-f3baeae448c3

## Description

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 Director, Data Analytics Overview: The Global Business Solutions Center (GBSC) Operational Excellence & Enablement organization advances enterprise performance by combining data, technology, analytics, and operational expertise. The team partners across GBSC and its stakeholders to establish trusted data foundations, develop forward-looking insights, and create scalable reporting capabilities that improve decision-making, operational visibility, and business outcomes. We are seeking a strategic and highly collaborative Director, Data Analytics to lead an integrated organization spanning Data Science, Data Architecture & Engineering, and Reporting & Insights. This leader will provide end-to-end accountability for the data and insights value chain, from architecture and data products through advanced analytics, reporting, and executive storytelling. The Director will translate business priorities into a cohesive data strategy, build durable capabilities, and ensure that solutions are trusted, scalable, governed, and connected to measurable business value. This role is designed for an enterprise-minded leader who can set direction, develop talent, simplify complexity, and move the organization from fragmented reporting toward proactive, predictive, and decision-oriented insights. Role: • Lead, coach, and develop the leaders responsible for Data Science, Data Architecture & Engineering, and Reporting & Insights, establishing clear accountability, priorities, operating rhythms, and performance expectations across the organization. • Define and execute a unified data and insights strategy aligned with GBSC Operational Excellence & Enablement priorities and the evolving needs of business stakeholders. • Own the end-to-end portfolio of data, analytics, and reporting initiatives to support operational excellence, balancing foundational investments, strategic use cases, regulatory and control requirements, and near-term business value. • Partner with functional leaders to translate ambiguous business challenges into clear data products, analytical use cases, reporting solutions, and decision-support capabilities. • Guide the design of scalable data architecture, engineering pipelines, semantic models, and reusable data products that improve data quality, accessibility, interoperability, and speed to insight. • Advance the organization from descriptive reporting toward diagnostic, predictive, and prescriptive insights through responsible application of statistical methods, machine learning, artificial intelligence, and automation. • Create and enforce standards for data quality, solution design, development, testing, documentation, deployment, monitoring, and lifecycle management in partnership with technology, risk, privacy, security, and governance teams. • Build a diverse, inclusive, and high-performing global team by strengthening succession plans, technical depth, leadership capability, and career pathways across all three disciplines. • Stay current on emerging data, analytics, AI, and reporting technologies, applying relevant innovations to improve team productivity, solution quality, and business impact. All About You: • Undergraduate degree in Data Science, Computer Science, Information Systems, Engineering, Statistics, Mathematics, Business, Finance, or a related field; advanced degree preferred. • Experience leading multidisciplinary data and analytics organizations, including leaders and teams across data

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