Staff Product Manager (Attribution)

StackAdapt is a technology company providing an AI-powered marketing platform for programmatic advertising and marketing channels. The Staff Product Manager will own the vision and roadmap for the Attribution stack, partnering with clients and cross-functional teams to develop attribution, reporting, and measurement capabilities and deliver high-quality products.

Responsibilities:

• Drive the vision and own the roadmap for our Attribution stack, covering click and view-through attribution, vertical and channel specific attribution models such as CTV and ABM, and several customer-facing reporting and measurement features
• Work with our largest and most complex clients to understand their attribution needs and how they think about assigning marketing credit
• Drive alignment across the teams that contribute to StackAdapt's attribution story (Data & Analytics, Data Science, Revenue, Product Marketing, etc.) and contribute to internal/external enablement on existing and new attribution methodologies
• Responsible for delivery of product specs that capture user needs along with clear direction for the engineer, design, and QA team on how the feature should behave and what success looks like
• Success for this role is someone who can drive features through to completion, delivering high-quality results while dealing with ambiguity, and creating products that drive more customer engagement with the StackAdapt platform

Requirements:

• Strong understanding of attribution methodologies across the broader advertising and measurement industry, beyond individual ad platform reporting, including but not limited to MTA, MMM, incrementally lift studies, geo experiments, CTV attribution, ABM attribution, retail media measurement, and web analytics attribution
• Demonstrated ownership of vision and roadmap end to end: shaping direction from ambiguous problems, aligning teams, and delivering measurable outcomes
• High technical fluency: able to translate complex constraints (data pipelines, identity resolution, event-level attribution at scale) into clear product decisions, and explain attribution and measurement concepts to non-technical audiences
• Bias for action grounded in data: you form hypotheses, ship experiments to test them, and iterate based on what the data says
• Keen design sense; you're able to look at a feature and understand it through a user's eyes
• You've successfully incorporated LLM usage into your day-to-day to accelerate your work, and understand where these tools can help customers versus where more deterministic methods are appropriate