The Coca-Cola Company
Head of Product Data & Analytics
The Coca-Cola Company, Atlanta, Georgia, United States, 30383
Join to apply for the
Head of Product Data & Analytics
role at
The Coca-Cola Company .
About the Role Digital products play a central role in how we create value for customers, support the teams who serve them, and shape the consumer experience. Our product organization brings together small, empowered teams that move with clarity, speed, and purpose, enabling digital to be a meaningful source of advantage across our operating unit. Our work touches on the experiences that keep the business running, including customer journeys, service delivery, sales workflows, and the systems that connect them. We are raising our standards for product craft and rebuilding the platforms behind these experiences. This role is deeply cross‑functional and is based in Atlanta, GA on a hybrid schedule.
Key Responsibilities
Build and lead the Data & Analytics practice
Hire, develop, and lead analysts, data scientists, and experimentation specialists embedded in product teams.
Define roles, standards, and career paths for analytics and data science.
Create a culture rooted in curiosity, rigor, and clear storytelling.
Make data foundational to product discovery and delivery
Ensure teams use data to understand behavior, measure outcomes, and evaluate ideas.
Guide the use of experiments, prototypes, and causal analysis to reduce risk.
Help product leaders shift from feature roadmaps to outcome‑based KPIs and scorecards.
Define measurement, instrumentation, and experimentation
Establish KPIs, guardrails, and leading indicators for each product area.
Operationalize experimentation practices including A/B tests, holdouts, and causal inference.
Ensure products are instrumented correctly so teams are never “flying blind.”
Lead core product analytics capabilities
Oversee user analytics, customer analytics, funnels, cohorts, and retention analyses.
Guide business analytics such as LTV, churn, and economics.
Ensure data quality, accuracy, and usability across platforms.
Develop and apply data science for insight and customer value
Guide segmentation, forecasting, clustering, and propensity modeling.
Partner with product and engineering to embed predictive and adaptive models into experiences.
Ensure ML models are monitored, evaluated, and continuously improved.
Elevate data capability across the organization
Coach PMs, designers, and engineers to be confident, data‑literate decision‑makers.
Promote experimentation and analytics as routine parts of product work.
Share learnings and insights broadly to create organizational knowledge.
Influence product strategy and portfolio decisions
Size opportunities, prioritize bets, and guide investment decisions using data.
Provide scenario modeling and forecasting for portfolio sequencing.
Represent the data and insights perspective in senior forums.
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 or modeling.
Education Requirements Bachelor’s degree; 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, and business goals; understands how metrics and models influence decisions across journeys, platforms, and teams.
Experimentation expertise: Designs and governs experiments that produce reliable, decision‑ready evidence and helps teams reduce risk and accelerate learning.
Data science fluency: Guides analysts and data scientists in applying advanced techniques such as segmentation, forecasting, clustering, and recommendations to deliver insight and customer value.
Insight storytelling and influence: Translates complex analyses into clear, compelling narratives that shape strategy, inform decisions, and align cross‑functional stakeholders.
Team leadership and capability building: Develops, coaches, and elevates analysts and data scientists; builds a culture of curiosity, rigor, and shared ownership of outcomes across product teams.
Work Authorization The Coca‑Cola Company will not offer sponsorship for employment status (including, but not limited to, H1‑B visa status and other employment‑based non‑immigrant visas) for this position. All applicants must be currently authorized to work in the United States on a full‑time basis and must not require sponsorship to continue to work legally in the United States.
Compensation Pay range: $195,500 – $226,800. 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 is a market‑based competitive value for your role. It falls in the middle of the range for your role, indicating performance at target.
Job Details
Seniority Level: Not Applicable
Employment Type: Full‑time
Job Function: General Business
Industries: Manufacturing, Food and Beverage Manufacturing, and Food and Beverage Services
#J-18808-Ljbffr
Head of Product Data & Analytics
role at
The Coca-Cola Company .
About the Role Digital products play a central role in how we create value for customers, support the teams who serve them, and shape the consumer experience. Our product organization brings together small, empowered teams that move with clarity, speed, and purpose, enabling digital to be a meaningful source of advantage across our operating unit. Our work touches on the experiences that keep the business running, including customer journeys, service delivery, sales workflows, and the systems that connect them. We are raising our standards for product craft and rebuilding the platforms behind these experiences. This role is deeply cross‑functional and is based in Atlanta, GA on a hybrid schedule.
Key Responsibilities
Build and lead the Data & Analytics practice
Hire, develop, and lead analysts, data scientists, and experimentation specialists embedded in product teams.
Define roles, standards, and career paths for analytics and data science.
Create a culture rooted in curiosity, rigor, and clear storytelling.
Make data foundational to product discovery and delivery
Ensure teams use data to understand behavior, measure outcomes, and evaluate ideas.
Guide the use of experiments, prototypes, and causal analysis to reduce risk.
Help product leaders shift from feature roadmaps to outcome‑based KPIs and scorecards.
Define measurement, instrumentation, and experimentation
Establish KPIs, guardrails, and leading indicators for each product area.
Operationalize experimentation practices including A/B tests, holdouts, and causal inference.
Ensure products are instrumented correctly so teams are never “flying blind.”
Lead core product analytics capabilities
Oversee user analytics, customer analytics, funnels, cohorts, and retention analyses.
Guide business analytics such as LTV, churn, and economics.
Ensure data quality, accuracy, and usability across platforms.
Develop and apply data science for insight and customer value
Guide segmentation, forecasting, clustering, and propensity modeling.
Partner with product and engineering to embed predictive and adaptive models into experiences.
Ensure ML models are monitored, evaluated, and continuously improved.
Elevate data capability across the organization
Coach PMs, designers, and engineers to be confident, data‑literate decision‑makers.
Promote experimentation and analytics as routine parts of product work.
Share learnings and insights broadly to create organizational knowledge.
Influence product strategy and portfolio decisions
Size opportunities, prioritize bets, and guide investment decisions using data.
Provide scenario modeling and forecasting for portfolio sequencing.
Represent the data and insights perspective in senior forums.
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 or modeling.
Education Requirements Bachelor’s degree; 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, and business goals; understands how metrics and models influence decisions across journeys, platforms, and teams.
Experimentation expertise: Designs and governs experiments that produce reliable, decision‑ready evidence and helps teams reduce risk and accelerate learning.
Data science fluency: Guides analysts and data scientists in applying advanced techniques such as segmentation, forecasting, clustering, and recommendations to deliver insight and customer value.
Insight storytelling and influence: Translates complex analyses into clear, compelling narratives that shape strategy, inform decisions, and align cross‑functional stakeholders.
Team leadership and capability building: Develops, coaches, and elevates analysts and data scientists; builds a culture of curiosity, rigor, and shared ownership of outcomes across product teams.
Work Authorization The Coca‑Cola Company will not offer sponsorship for employment status (including, but not limited to, H1‑B visa status and other employment‑based non‑immigrant visas) for this position. All applicants must be currently authorized to work in the United States on a full‑time basis and must not require sponsorship to continue to work legally in the United States.
Compensation Pay range: $195,500 – $226,800. 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 is a market‑based competitive value for your role. It falls in the middle of the range for your role, indicating performance at target.
Job Details
Seniority Level: Not Applicable
Employment Type: Full‑time
Job Function: General Business
Industries: Manufacturing, Food and Beverage Manufacturing, and Food and Beverage Services
#J-18808-Ljbffr