Data Product Manager

Summary

Join Carter, a company rethinking adtech infrastructure with a privacy-first, AI-powered platform, as their Data Product Manager. You will shape data-driven products supporting bidding, targeting, insights, optimization, and measurement. This role requires close collaboration with engineering, data science, UX, and GTM teams to launch and scale impactful products. Candidates with adtech experience in high-frequency, high-volume settings are encouraged to apply. The position offers a competitive salary, strong healthcare insurance and benefits, and a hybrid work model (ideally 2 days/week in the Toronto office, but remote applications across North America are accepted). Carter prioritizes employee growth, providing extensive learning and development resources.

Requirements

• 3–6 years of product management experience, ideally in ad tech, martech, or data platforms
• Experience with DSPs, SSPs, CDPs, DMPs, or similar ecosystems is a huge plus
• Strong understanding of how data pipelines, ML models, and APIs work, not just what they do, but how they do it
• Excellent communicator who can drive alignment between technical and non-technical stakeholders
• Passionate about solving real user problems with data, not just building dashboards
• Familiar with tools like Looker, Snowflake, dbt, Python, Postgres, or similar, you don't have to code, but you get it
• Previous experience working in a startup or fast-paced agile environment

Responsibilities

• Own and evolve the product roadmap for data and measurement features (e.g., performance models, audience tools, reporting layers, campaign optimization)
• Work closely with data engineering and ML teams to define product requirements, success metrics, and delivery timelines
• Translate advertiser use cases into data product specs and interfaces
• Partner with account and strategy teams to gather feedback and define high-impact use cases
• Understand how models work (propensity, LTV, lookalike, pacing, bidding, etc.) and ensure they are integrated in ways that users trust and value
• Ensure data flows are robust, privacy-safe, and usable across the ad stack (DSPs, SSPs, CDPs, retail platforms)
• Define product metrics and validate outcomes through experimentation and feedback loops

Benefits

• Competitive salary
• Strong healthcare insurance
• Benefits package
• Extensive learning and development resources