Senior Product Manager - Retail Platforms

The Senior Product Manager for Retail Platforms will shape data and intelligence capabilities that support Transaction Growth across Coca-Cola’s retail environment. The role partners across business, data science, engineering, and seller frontline teams to define outcomes, build measurement and learning loops, and improve recommendation quality over time.

Role Location

Atlanta, GA (onsite), United States of America.

Compensation

Base salary: USD 171,000 - 198,000 per year.

• Annual incentive: Reference value 30%
• Long-term incentive: Reference value 0% - 20%
• Pay range: United States: USD 171,000 - 198,000

Travel and Relocation

• Travel required: 0% - 25%
• Relocation provided: Yes

Responsibilities

• Own the vision, outcomes, and roadmap for Retail Transaction Growth data and intelligence capabilities.
• Define business and user problems to solve, and establish measurable outcomes for success.
• Align Retail priorities with the data, models, and technical capabilities required to deliver them.
• Balance foundational investments in data and technology with near-term opportunities that create value for sellers.
• Use market evidence to reassess priorities and determine where the team should invest.
• Treat data, models, and decisioning capabilities as product offerings, with defined users, outcomes, quality expectations, and measures of success.
• Partner with engineering to understand how data is sourced, transformed, connected, and delivered to products, and make architecture, pipeline, API, quality, and reliability trade-offs.
• Work with data science to define what makes a recommendation or prediction useful and how to evaluate model performance.
• Determine the signals needed to assess relevance, seller action, and downstream results.
• Build feedback loops so market behavior and outcomes improve future recommendations.
• Spend time with sellers and commercial teams to understand workflows, decisions, and where improved data or intelligence can help.
• Lead discovery through field research, data analysis, experimentation, prototyping, and testing.
• Translate discoveries into clear priorities and product requirements.
• Collaborate closely with engineering, data science, and design to deliver solutions that are valuable, usable, feasible, and viable.
• Define measurement up front and use results to decide what to improve, scale, change, or stop.
• Make considered trade-offs when evidence is incomplete and priorities compete.
• Convert complex data and model outputs into guidance sellers can understand and act on.
• Develop a deep understanding of seller workflows to ensure recommendations fit naturally into how work is done.
• Enable sellers to focus on what action to take and why it matters, without requiring them to understand recommendation complexity.
• Use seller behavior and market outcomes to identify where the product performs and where it needs improvement.
• Move effectively across commercial, product, data science, engineering, and design discussions.
• Translate business needs into terms technical teams can implement, and technical constraints into choices business partners can evaluate.
• Communicate product vision, priorities, decisions, and trade-offs clearly.
• Build cross-team alignment without relying on formal authority.
• Support a culture centered on evidence, experimentation, learning, and measurable outcomes.

Required Qualifications

• 5+ years of experience in product management or a related discipline such as data, analytics, data science, engineering, or strategy.
• Experience building or managing data-intensive products, platforms, or capabilities.
• Technical depth to engage in decisions involving data architecture, pipelines, APIs, data models, machine-learning models, data quality, and measurement.
• Proven ability to translate business problems into product and technical requirements.
• Experience working closely with data scientists and engineers to make product decisions and trade-offs.
• Strong analytical and problem-solving skills, including using data and experimentation to guide decisions.
• Experience defining product outcomes and determining measurable value creation.
• Ability to operate effectively in ambiguous environments with evolving requirements and incomplete information.
• Strong communication skills across technical, commercial, and executive audiences.

Preferred Qualifications

• Experience owning data products, recommendation systems, decision-support products, or AI/ML-enabled products.
• Working knowledge of modern data architectures and how data moves from source systems through pipelines, services, and models into user-facing products.
• Experience partnering with data science teams on model development, validation, deployment, and improvement.
• Experience designing feedback loops where user behavior and downstream outcomes inform future recommendations.
• Experience with experimentation, model evaluation, or other methods for understanding incremental value from recommendations.
• Experience building products for frontline sales, sales enablement, retail execution, or other field-based users.
• Experience simplifying sophisticated analytics or intelligence for nontechnical users.
• Experience balancing longer-term platform investments with immediate product and business needs.

Education

Bachelor’s degree or equivalent practical experience. An advanced degree in business, computer science, engineering, data science, analytics, or a related field is a plus.

Technologies

• Microsoft Azure
• Microsoft Office

Benefits

• A full range of medical, financial, and/or other benefits, dependent on the position, is offered.

Application Details

Job posting end date: October 23, 2026