Head of Product Data & Analytics at The Coca-Cola Company

Atlanta, Georgia, United States -

Full Time

Start Date

Immediate

Expiry Date

19 Apr, 26

Salary

226800.0

Posted On

19 Jan, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Analytics, Data Science, Product Analytics, Experimentation, Statistical Techniques, Collaboration, Influence, Leadership, Data Literacy, Curiosity, Storytelling, Measurement Frameworks, Customer Value, Segmentation, Forecasting, Causal Analysis

Industry

Food and Beverage Services

Description

Location(s): United States of America City/Cities: Atlanta Travel Required: 00% - 25% Relocation Provided: Yes Job Posting End Date: January 30, 2026 Shift: Job Description Summary: This is a People Leader role. The incumbent must be based in Atlanta, GA and work a hybrid work schedule 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. About the Role The Head of Product Data & Analytics leads the data discipline within the Product organization, overseeing the analysts and data scientists embedded in empowered product teams. This leader is responsible for how teams use data to understand behavior, measure progress, experiment confidently, and discover new opportunities. You will build and scale a modern product insights capability that brings together analytics, data science, experimentation, instrumentation, and decision support. You will ensure teams move from opinion-driven to evidence-informed, while partnering closely with Design and Research to connect what users do with why they do it. This role is deeply cross-functional. You will work alongside Product, Design, and Engineering leaders to define metrics, build measurement frameworks, instrument features, run experiments, and develop models that create both internal insight and customer-facing value. 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. 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. Skills: 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 Percentage: 30 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. 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. The Coca-Cola Company is a global community of passionate employees who are refreshing the world and making a difference every day. Innovation has been at the heart of our story since 1886. It goes beyond new flavors and brands. Learn more about our system and how we’re making an impact. We believe a diverse, equitable and inclusive workplace makes us a stronger and more innovative company. This includes supporting the financial and personal well-being of our employees. Learn more about our benefits. We empower each and every one of our employees across the globe to prioritize their career development by building capabilities, developing new skills, and leaning into new experiences. Learn how we provide support and clarity on defining your own career so you can thrive. We’re glad you’ve chosen to explore your next career opportunity with The Coca-Cola Company. Learn more about our hiring process and pick up tips on how to showcase your experience and skills so you can stand out and thrive.

Responsibilities

The Head of Product Data & Analytics leads the data discipline within the Product organization, overseeing analysts and data scientists. This role involves building a modern product insights capability and ensuring teams use data effectively to drive product decisions.