Data Product Manager, Retail Media

At Circle K, our mission is simple: to make our customers’ lives a little easier every day. Whether you have stopped by for a coffee, refueled your car, or grabbed something to eat on the go, you already know who we are.

Full Circle Media is Circle K’s in-house retail media and data monetization engine - built to accelerate customer acquisition, increase traffic, and drive incremental sales for both brands and our business. We are creating a unified, global retail media platform that brings together in‑store screens, offsite media activation, and privacy first data products - all powered by rich first‑party insights.

vRole Overview

Audience Strategy & Activation

• Define, own, and evolve a standardized audience of taxonomy across the enterprise to ensure consistency in segmentation, activation, and reporting.
• Build and scale high-value customer audiences using first-party data, behavioral signals, and predictive modeling.
• Ensure seamless audience activation across digital, in-store, and offsite media ecosystems.

Measurement & Attribution

• Design and operationalize robust measurement frameworks that connect media exposure to business outcomes (e.g., sales lift, basket size, frequency).
• Establish measurement activation pipelines to support both onsite and offsite media channels, ensuring consistent tracking and attribution across the ecosystem.
• Implement multi-touch attribution and closed-loop measurement using transaction-level data.
• Standardize reporting methodologies to provide advertisers with consistent, transparent insights.

Incrementality & Experimentation

• Lead incrementality testing (A/B, geo-lift, holdout groups) to quantify true campaign impact.
• Establish test-and-learn frameworks that optimize audience strategies and media performance.

Performance Insights & Feedback Loops

• Develop audience performance feedback loops that continuously inform and refine audience definitions, targeting strategies, and budget allocation.
• Deliver actionable insights to advertisers and internal stakeholders, linking campaign performance to customer behavior.
• Build intuitive dashboards and self-serve analytics tools for campaign visibility.

Key Responsibilities

Roadmap & Strategy

• Team Leader: Lead a team of motivated Data Product Specialists
• Partner closely with the Group Product Manager to define and execute the data product vision, roadmap, and backlog
• Collaborate cross functionally with Retail Media Sales, Ad Operations, Store Operations, Legal, and Privacy teams
• Translate business and advertiser needs into data solutions, including metric definitions, data models, and scalable self-service analytics and data products.
• Own delivery of key data components across the retail media platform, spanning in-store media, offsite media integrations, campaign tooling, measurement, and data monetization - working closely with other Product Managers to deliver a cohesive, end-to-end RMN experience.

Data Integration & Engineering Coordination

• Partner with Ad Operations to validate correct implementation of ad tags, inventory configuration, and event level tracking in advanced Ad serving environments
• Coordinate with Data Engineering to import data from enterprise DSP (Demand Side Platforms) used for programmatic media buying, and ad‑serving and yield management platforms used for publisher operations

Governance & Insight Enablement

• Own and maintain the data catalog and lineage documentation to improve data discoverability, trust, and self‑service adoption across teams.
• Liaise with Product Performance Analytics to deliver certified datasets on time for monthly leadership dashboards and ad-hoc reporting.

Skills Required

• Strong team leader with the ability to balance strategic thinking and pragmatic execution, while remaining responsive to evolving business needs
• Excellent communicator in English, able to translate complex concepts for technical and non-technical stakeholders.
• Customer-obsessed problem solver who collaborates across geographies and levels.
• Curious lifelong learner with a passion for retail, loyalty programs, and emerging analytics techniques.

Qualifications & Experience

• Advanced degree in Engineering, Data Science, or related analytical field.
• 7+ years of experience across one or more areas: data engineering, data analytics, or data architecture.