Staff Product Manager, Ads Optimization

Nextdoor
US Remote$170k – $250kPosted 16 March 2026

Tech Stack

Job Description

#TeamNextdoor Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 340,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com . Meet Your Future Neighbors The Monetization Team at Nextdoor empowers businesses of all sizes to connect meaningfully with their local communities. Our advertising platform helps marketers reach the right audiences, drive measurable outcomes, and scale their growth efficiently. As Staff Product Manager, Ads Optimization, you will lead the strategy and roadmap for how campaigns deliver performance at scale. You will define and evolve our bidding systems, budget pacing frameworks, delivery optimization, and intelligent automation capabilities ensuring advertisers maximize outcomes while preserving a high-quality neighbor experience. This is a highly technical and strategic role at the center of our Ads ecosystem. You’ll partner deeply with Engineering, Data Science, and Revenue teams to shape how our auction, pacing, and ML-driven optimization systems evolve. Your work will directly impact advertiser ROI, revenue growth, and platform efficiency. At Nextdoor, we offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The hiring team will go over these expectations with you if you are being considered for a role near one of our offices in San Francisco, Los Angeles, Chicago, Dallas, New York, and London. The Impact You’ll Make Your responsibilities will include: Define and own the vision and roadmap for campaign optimization, including bidding algorithms, pacing systems, auction dynamics, and automation capabilities Partner with Data Science, Engineering and ML to shape experimentation strategy, define model success criteria, and translate model performance into advertiser value Develop and own advertiser experience for campaign delivery optimization features that reduce friction and improve advertiser outcomes Collaborate with Sales and Product Marketing to ensure optimization capabilities are intuitive, explainable, and compelling to advertisers Influence cross-functional alignment on tradeoffs between short-term performance gains and long-term architectural investments Present strategy, impact, and performance insights to senior leadership, serving as the strategic voice for Ads Optimization across the organization Participate in in-person Nextdoor events such as trainings, off-sites, volunteer days, and team building exercises Build in-person relationships with team members and contribute to Nextdoor’s company culture What You’ll Bring to The Team 7+ years of product management experience, with 3+ years of experience in advertising technology and marketplace optimization Deep understanding of ads auction dynamics, bid optimization, budget pacing, and delivery systems Comfortable discussing ML models, experimentation frameworks, ranking systems, and system architecture with engineers and data scientists Strong cross-functional leadership, able to drive alignment across Engineering, Data Science, Revenue, and Marketing without heavy process Clear point of view on how automation and AI can transform advertiser outcomes Strong written and verbal communication skills; able to influence executives and explain technical concepts clearly Eagerness to explore and apply AI and emerging technologies to reimagine how work gets done Rewards Compensation, benefits, perks, and recognition programs at Nextdoor come together to create our total rewards package. Compensation will vary depending on your relevant skills, experience, and qualifications. The starting salary for this r ... (truncated, view full listing at source)
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