Head of Product Data & Analytics

The Coca-Cola Company is building a modern product organization for a business that operates at extraordinary scale. We are building the digital product foundation for how we serve customers, enable teams, and grow the business in the years ahead. Data and analytics are central to that ambition, helping teams understand what is happening, why it matters, and where to act next.

This role will help build the intelligence layer behind our product organization: the measurement, experimentation, analytics, data science, and decision-support capabilities that help teams learn faster, make better decisions, and create measurable customer and business value.

About the Role

The Head of Product Data & Analytics leads the data discipline within the Product organization, overseeing analysts and data scientists embedded in empowered product teams.

You will build and scale a modern product insights capability that connects product analytics, experimentation, instrumentation, decision support, and data science. Working closely with Product, Design, and Engineering, you'll help teams connect what users do with why they do it, and translate those insights into better products, stronger decisions, and measurable outcomes.

This is a cross-functional leadership role focused on shaping how Coca-Cola's product teams learn, prioritize, and create value through data.

Responsibilities

Build and lead the Product Data & Analytics practice

• Hire, develop, and lead analysts, data scientists, and experimentation specialists embedded in product teams

• Define roles, standards, tools, operating rhythms, and career paths for analytics and data science within the product organization

• Build a culture rooted in curiosity, rigor, clear storytelling, and shared ownership of outcomes

Make data foundational to how product teams work

• Ensure teams use data to understand user behavior, measure outcomes, evaluate ideas, and identify new opportunities

• Help product leaders move from feature roadmaps to outcome-based KPIs, scorecards, and learning agendas

• Partner with Design and Research to connect behavioral data, qualitative insight, and business context

Define measurement, instrumentation, and experimentation

• Establish KPIs, guardrails, leading indicators, and measurement frameworks for each product area

• Ensure products are instrumented effectively so teams can understand adoption, engagement, friction, and impact

• Operationalize experimentation practices, including A/B tests, holdouts, causal inference, and other methods appropriate to real-world product environments

Lead core product analytics capabilities

• Oversee user analytics, customer analytics, funnels, cohorts, retention, adoption, and behavioral analyses

• Guide business analytics such as lifetime value, churn, economics, and value realization

• Ensure data quality, accuracy, consistency, and usability across product platforms and reporting environments

Develop and apply data science for insight and product value

• Guide segmentation, forecasting, clustering, propensity modeling, recommendations, and other advanced analytics approaches

• Partner with Product and Engineering to embed predictive, adaptive, and intelligent capabilities into product experiences

• Ensure models are monitored, evaluated, explained, and continuously improved

Elevate data capability across the organization

• Coach PMs, designers, engineers, and business partners to become more confident, data-literate decision-makers

• Make analytics, experimentation, and learning a routine part of product team practice

• Share insights broadly to build organizational knowledge and improve portfolio-level decision-making

Influence product strategy and portfolio decisions

• Size opportunities, prioritize bets, and guide investment decisions using data

• Provide scenario modeling, forecasting, and evidence to inform portfolio sequencing

• Partner with product leadership to ensure strategy is grounded in customer behavior, business value, and measurable outcomes

Key Qualifications

• 10+ years of experience in analytics, data science, or related fields, with at least five years leading teams in digital product environments

• Experience embedding analysts and/or data scientists within cross-functional product or engineering teams

• Strong foundation in product analytics including behavioral data, funnels, cohorts, and retention

• Deep experience with experimentation including A/B testing, test design, and interpretation

• Familiarity with data science techniques such as clustering, regression, propensity modeling, and recommendations

• Comfort with modern data platforms including warehouses, event tracking, BI tools, and experimentation frameworks

• Ability to translate complex analyses into clear, actionable insights for product and executive audiences

• Strong collaboration and influence skills across Product, Engineering, and Design

Preferred Qualifications

• Experience building or scaling data and analytics within empowered product team models

• Background applying causal inference or quasi-experimental methods in real-world environments

• Exposure to embedding ML models into customer-facing products

• Familiarity with AI and agentic systems as accelerators for analysis, modeling, experimentation, workflow automation, or product decisioning

Education: Bachelor's degree required; Advanced degree in data science, statistics, economics, computer science, or a related field preferred.

Skills

• Analytical rigor: Applies strong statistical and analytical judgment to define, measure, and interpret product outcomes with clarity and precision.

• Product and systems thinking: Connects data, behavior, workflows, and business goals to understand how products create value across teams and platforms.

• Experimentation expertise: Designs and governs experiments that produce reliable evidence and help teams reduce risk and accelerate learning.

• Data science fluency: Guides advanced analytics and modeling approaches that deliver insight, decision support, and product value.

• Insight storytelling and influence: Translates complex analyses into clear narratives that shape strategy, inform decisions, and align stakeholders.

• Team leadership and capability building: Develops strong analytics and data science talent while building a culture of curiosity, rigor, and shared ownership of outcomes.

The Coca-Cola Company will not offer sponsorship for employment status (including, but not limited to, H1-B visa status and other employment-based nonimmigrant visas) for this position. Accordingly, all applicants must be currently authorized to work in the United States on a full-time basis and must not require The Coca-Cola Company's sponsorship to continue to work legally in the United States.

Pay Range:

United States of America: 224,100 USD - 257,600 USD

Base pay offered may vary depending on geography, job-related knowledge, skills, and experience. A full range of medical, financial, and/or other benefits, dependent on the position, is offered.

Annual Incentive Reference Value Percentage:

50

Annual Incentive reference value is a market-based competitive value for your role. It falls in the middle of the range for your role, indicating performance at target.

Long-term Incentive Reference Value Percentage:

20

Long-term Incentive reference value is a market-based competitive value for your role.

Location(s):

United States of America

City/Cities:

Atlanta

Travel Required:

00% - 25%

Relocation Provided:

Yes

Job Posting End Date:

June 26, 2026

Our Purpose and Growth Culture:

We are taking deliberate action to nurture an inclusive culture that is grounded in our company purpose, to refresh the world and make a difference. We act with a growth mindset, take an expansive approach to what's possible and believe in continuous learning to improve our business and ourselves. We focus on four key behaviors - curious, empowered, inclusive and agile - and value how we work as much as what we achieve. We believe that our culture is one of the reasons our company continues to thrive after 130+ years. Visit Our Purpose and Vision ( to learn more about these behaviors and how you can bring them to life in your next role at Coca-Cola.

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran, and basis of disability or any other federal, state or local protected class. When we collect your personal information as part of a job application or offer of employment, we do so in accordance with industry standards and best practices and in compliance with applicable privacy laws.Pay Range:United States of America: 0 USD - 0 USDBase pay offered may vary depending on geography, job-related knowledge, skills, and experience. A full range of medical, financial, and/or other benefits, dependent on the position, is offered.Annual Incentive Reference Value Percentage:50Annual Incentive reference value is a market-based competitive value for your role. It falls in the middle of the range for your role, indicating performance at target.Long-term Incentive Reference Value Percentage:20Long-term Incentive reference value is a market-based competitive value for your role

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran, and basis of disability or any other federal, state or local protected class.