Sr. Product Manager, Ads Quality Delivery

Pinterest•Palo Alto, CA

3d•$139,764 - $287,749•Remote

About The Position

The Sr. Product Manager, Ads Quality Delivery will help Pinterest’s Ads Quality team show Pinners the right ad at the right time, balancing value for Pinners, advertisers, and Pinterest. The role owns product vision and delivery for capabilities in ads quality and delivery, translating business problems into business and technical requirements, maintaining a prioritized roadmap and requirements backlog, and coordinating work from discovery through general availability and adoption. The Product Manager will work on back-end ads delivery systems and ads bidding and optimization solutions. This includes coordinating changes to components such as retrieval, ranking, pacing and budgeting, auction and bidding, quality and diversity guardrails, conversion visibility, forecasting, modeling, and measurement. The role partners with engineering, machine learning, data science and analytics, design, research, PMM, sales, policy and integrity, and other product managers to align architecture, APIs and contracts, experiments, guardrails, dependencies, launches, and feedback loops. Success includes delivering measurable advertiser and Pinner outcomes while maintaining a safe, delightful Pinner experience. The position can be based anywhere in the United States and requires in-office collaboration 1–2 times per quarter. It is not eligible for relocation assistance. The role offers a base salary range of $139,764–$287,749 USD and is also eligible for equity.

Requirements

At least 4 years of experience as a Product Manager, Engineering Manager, Data Scientist, or in a related role.
Evidence of ability to review and define products and strategies for back-end products in ambiguous spaces and execute from ideation and roadmap development through go-to-market.
Experience working cross-functionally with engineering, data, or PMM teams.
Ability to empathize with, anticipate the needs of, and collaborate effectively with diverse stakeholders.
Deep understanding of business metrics and tradeoffs in online marketplaces.
Experience with Ads Marketplace and/or Ads Formats.
Bachelor’s degree in a relevant field such as Computer Science, or equivalent experience.

Nice To Haves

Direct experience with and fundamental understanding of ads delivery systems.
Experience designing, running, or analyzing marketplace experiments.

Responsibilities

Own a vision for new and existing capabilities that match the right ad to the right Pinner at the right time.
Translate problem statements into clear business and technical requirements using BRDs and PRDs, including epics, user stories, and acceptance criteria.
Create and maintain a prioritized roadmap and requirements backlog; track requirements from discovery through general availability and ensure traceability from business goals to shipped features.
Plan and deliver a sequenced roadmap, aligning with partner teams on architecture, guardrails, and experimentation to drive measurable advertiser and Pinner outcomes.
Coordinate changes to back-end ads delivery components, including retrieval, ranking, pacing and budgeting, auction and bidding, quality and diversity guardrails, conversion visibility, forecasting, modeling, or measurement.
Partner with engineering, ML, data science and analytics, design, and research to deliver features; collaborate with PMM, sales, and policy and integrity as needed for launches.
Coordinate with Ads Quality and front-end product peers on dependencies, APIs and contracts, experiment design and guardrails, go-to-market plans, and feedback loops.
Facilitate roadmap and requirements reviews; maintain shared roadmaps, PRDs, and dependency trackers; surface risks, decisions, and changes proactively.
Build features for ads bidding and optimization that help advertisers express objectives and align budgets with business needs while maintaining a safe, delightful Pinner experience.
Deliver scoped improvements from discovery through launch and adoption, instrument metrics, document work, and incorporate learnings into subsequent iterations.
Define success metrics and acceptance criteria upfront, track requirement completion and post-launch quality signals, and use insights to update the roadmap.