Senior Vice President, Data Strategy & Analytics

LEARFIELD•Irvine, CA

2d•$250,000 - $300,000

About The Position

We are the leading media and technology company powering college athletics— holding the largest first-party college athletics fan database in the world. Our platform connects fans, schools, and brand partners across the full fan journey, creating a powerful data ecosystem spanning ticketing, fundraising, digital engagement, sponsorship, marketing, and fan behavior. As Learfield continues to invest in data and AI, we are seeking a strategic executive to transform this unmatched data asset into a competitive advantage. The Senior Vice President, Data Strategy & Analytics will define our enterprise data strategy, accelerate commercialization through data products and AI, and deliver actionable insights that strengthen relationships with school partners, empower sponsorship sales, and drive measurable business growth.

Requirements

15+ years of experience in data, analytics, or data engineering, including significant time in senior leadership roles.
Demonstrated experience building and leading multidisciplinary teams (engineering, product, and analytics) of people across both enterprise data architecture and data products — not just one or the other.
Hands-on experience with leading cloud data providers such as Snowflake or Databricks is required.
Experience applying LLMs and other AI-native approaches to make data accessible and actionable.
Demonstrated success using data to power personalization, fan/customer engagement, and revenue generation.
Strong grounding in data governance, privacy, and security for large-scale consumer and transactional data.
Excellent executive communication and stakeholder management, including client-facing experience.

Nice To Haves

Hands-on familiarity with data clean rooms and privacy-safe data collaboration.
Experience in live events, sports, ticketing, fundraising/donations, or college athletics.
Background in ad tech, MarTech, and/or sponsorship measurement.
Experience commercializing data products in a B2B software environment.

Responsibilities

Define and execute Learfield's enterprise data strategy, aligning data, AI, engineering, and product investments with business growth and client outcomes.
Lead, develop and evolve a team of 15+ across product managers, data engineers, and BI analysts —while evaluating organizational structure and capabilities to support future growth.
Effectively partner with executive, product, sales, and client-facing teams to translate data capabilities into commercial value and competitive differentiation.
Own and evolve Learfield's enterprise data platform spanning fan identity, ticketing, donations, digital engagement, sponsorship, campaign, and marketing data to create a scalable foundation for analytics, activation, and commercialization.
Establish strong data governance, quality, privacy, and compliance practices appropriate for handling large volumes of consumer and transactional data.
Build and operate data clean rooms to enable secure, privacy-safe data collaboration with sponsors, partners, and clients.
Drive a product-led approach to data by developing scalable products that create measurable value for schools, brand partners, sponsorship sales, and internal stakeholders.
Advance audience segmentation and personalization capabilities that improve fan engagement, ticket sales, fundraising, sponsorship activation, and digital marketing performance.
Leverage data to unlock new sponsorship opportunities, improve campaign measurement, enable premium sponsorship pricing, and create new revenue opportunities for Learfield and its partners.
Deliver analytics and BI that quantify fan engagement and revenue generation and clearly demonstrate ROI to clients.
Serve as a senior, credible voice with strategic clients and partners on data strategy, capabilities, and value.
Guide the team to build native-AI sematic layers across disparate datasets leveraging agentic AI — LLM-powered interfaces, natural-language querying, and intelligent data services that make insights accessible to non-technical users.
Define the common data model and semantic layer that connects fan, ticketing, donation, campaign, web, email, and partner data into trusted metrics, reusable segments, and activation-ready audiences.