Manager, Digital Applied Analytics

Job Description

Who is Taco Bell?

Taco Bell was born and raised in California and has been around since 1962. We went from selling everyone's favorite Crunchy Tacos on the West Coast to a global brand with 8,500+ restaurants, 350 franchise organizations, that serve 42+ million fans each week around the globe. We're not only the largest Mexican-inspired quick service brand (QSR) in the world, we're also part of the biggest restaurant group in the world:
Yum! Brands.

Much of our fan love and authentic connection with our communities are rooted in being rebels with a cause. From ensuring we use high quality, sustainable ingredients to elevating restaurant technology in ways that hasn't been done before... we will continue to be inclusive, bold, challenge the status quo and push industry boundaries.

We're a company that celebrates and advocates for different, has bold self-expression, strives for a better future, and brings the fun while we're  fuel our culture with real people who bring unique experiences. We inspire and enable our teams and the world to Live Más.

At Taco Bell, we're Cultural Rebels. Want to join in on the passion-fueled fun? Learn more about the career below.

About the Job:

This role leads the Digital Customer Data & Analytics team, reporting to the Director of Digital Customer Data & Analytics, and will manage 3-4 direct reports. It is a highly technical leadership position requiring recent, hands-on experience in data engineering practices, infrastructure design, and advanced analytics. The candidate must demonstrate expert-level SQL proficiency, intermediate Python skills, and exposure to ML/AI, as technical work cannot be delegated and must be executed personally for speed and accuracy.

Beyond technical execution, the role will shape the vision for applied analytics, drive roadmap implementation, and coach junior team members to deliver impactful, data-driven insights that influence strategic decisions across digital platforms. This position will have significant impact by ensuring analytics excellence and enabling faster, smarter decisions that align with organizational priorities.

The Day-to-Day:

• Lead and manage a team of digital customer analysts to build and support digital customer analytics across the organization.
• Own the development and execution of impactful deliverables with data-drive insights that inform strategic decision-making across creative, technical, and business stakeholders.
• Explore, scope, perform discovery, build, and implement new and current data models for baseline reporting and direct application of data model outputs to digital pillars. Work closely and knowledgably with data engineers to pipe data and data science teams to build data models, along with cross-functional partners to design domain-specific analytics frameworks.
• Ensure high data accuracy across all data platforms through regular data audits across all data sources and be able to knowledgably discovery, document, and ensure completion of outstanding data issues.
• Ensure that foundational analytics work aligns closely and is relevant with broader organization goals and big bets across the different domains.
• Support best-practice A/B testing and experimentation with a clear understanding of complex statistical concepts and methodologies (Bonferroni, Bayesian, etc.)
• Personally perform technical analytics utilizing SQL/Python at an expert level proficiency.
• Understanding of UAT/PVT methodologies and best practices to ensure proper governance, taxonomy, and implementation on digital platforms.

Is This You?

• Bachelor's/Master's degree in technical field (Math, STEM, Economics, Statistics, etc.)
• 8+ years of analytics experience, preferably with a focus on app/web or ecommerce data.
• 6+ years of hands-on experience designing, building, and applying various data models (multi-touch attribution, mixed marketing, churn, etc.)
• 8+ years of hands-on experience with SQL (expert proficiency)
• 5+ years of hands-on experience with Python (intermediate proficiency)
• Strong understanding of data architecture design, data pipelines, and data storage
• Strong understanding of data validation and QA both on digital platforms and…