Staff Product Manager (Attribution)
New
J
JobgetherAdTech, Data Analytics
Remote-first flexibility for candidates based in the United StatesFull-TimeStaff
Salary$168,000–$231,000 USD
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Job Details
- Required Skills
- Artificial IntelligenceProduct ManagementLLMData analytics
Requirements
- Strong product management experience with demonstrated end-to-end ownership of product vision and roadmaps in adtech, marketing measurement, or data-intensive environments.
- Deep understanding of advertising attribution methodologies including multi-touch attribution (MTA), marketing mix modeling (MMM), incremental lift studies, geo experiments, CTV attribution, ABM attribution, and web analytics attribution.
- Ability to shape product direction from ambiguous problems and align diverse stakeholders.
- Strong technical fluency in complex data systems, identity resolution, event-level attribution, and data pipelines.
- Ability to explain sophisticated attribution and measurement concepts to technical and non-technical audiences.
- Data-driven approach to forming hypotheses, running experiments, and iterating product decisions.
- Strong product and design judgment with a focus on user-centric usability.
- Practical experience incorporating LLMs and AI tools into day-to-day workflows.
- Strong communication, prioritization, and cross-functional collaboration skills.
Responsibilities
- Own the vision and roadmap for the Attribution product stack, including click-through and view-through attribution, vertical- and channel-specific models such as CTV and ABM, and customer-facing reporting and measurement capabilities.
- Work directly with large and complex clients to understand their attribution requirements, how they evaluate marketing performance, and how they determine which advertising interactions should receive credit for conversions.
- Build alignment across teams contributing to attribution and measurement, including Data & Analytics, Data Science, Revenue, Product Marketing, and other stakeholders.
- Develop clear and comprehensive product specifications that capture user needs and provide engineering, design, and QA teams with actionable direction.
- Lead product initiatives from ambiguous problems through delivery, making informed decisions and managing dependencies.
- Translate complex technical challenges, including data pipelines, identity resolution, and event-level attribution at scale, into clear product decisions and practical solutions.
- Use data to develop hypotheses, design and ship experiments, evaluate results, and continuously refine product direction.
- Incorporate AI and LLM-enabled workflows into product development where they can accelerate productivity.
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