Staff Product Manager, Advertiser Recommendations & Incentives

Snap Inc.•Los Angeles, CA

1d•$195,000 - $343,000•Onsite

About The Position

Snap Inc. is seeking a Staff Product Manager to lead the Advertiser Recommendations & Incentives platform within the SMC Ads team. This role involves owning the strategy, roadmap, and execution for the intelligence layer that understands advertiser needs and guides them towards performance and growth. The position requires deep collaboration with various teams across the ads stack, focusing on product intelligence, advertiser experience, and revenue growth. The ideal candidate will build data-backed recommendations and incentive programs to support advertisers at all stages and tiers.

Requirements

BS/BA degree or equivalent relevant experience
8+ years of experience in consumer or digital advertising products, with part of that experience in advertiser-facing or growth products
Experience working on data-backend ad platform products
Experience working across advertiser tiers, particularly SMC
Strong data fluency, including hands-on experience with SQL
Strong understanding of the digital advertising ecosystem, advertiser lifecycle, and the levers that drive campaign performance and advertiser retention.
Experience building recommendation, nudge, or personalization systems — with an ability to think through relevance, timing, and impact at scale.
Systems thinking across advertiser segmentation, data infrastructure, and product surfaces — with the ability to connect signals across the full advertiser journey.
Proven ability to collaborate across product, engineering, data science, and go-to-market teams in a complex, matrixed organization.
Revenue-focused mindset with a track record of building products that drive measurable advertiser and business outcomes.
Strong analytical skills with experience using data and experimentation to inform product decisions.
Excellent communication and influence skills, with the ability to drive alignment across stakeholders at all levels.
Ability to drive projects from strategy through to execution, balancing long-term vision with near-term delivery.

Nice To Haves

Experience building advertiser-facing recommendations, alerts, or performance intelligence products
Familiarity with CRM systems and how sales and AM workflows intersect with product data (e.g., Salesforce integration)
Experience working at the intersection of product and go-to-market, with meaningful exposure to sales or account management workflows

Responsibilities

Own the end-to-end strategy, roadmap, and execution for the advertiser recommendations and incentives platform, spanning all advertiser segments and tiers.
Define and evolve the intelligence layer that identifies where advertisers are in their journey and surfaces the right recommendations, treatments, and incentives to drive action and growth.
Build data-backed recommendation systems that unlock performance opportunities — from campaign setup and optimization nudges to growth levers tied to revenue outcomes.
Design and optimize incentive programs that drive advertiser activation, engagement, and spend milestones — ensuring incentives are well-targeted, measurable, and tied to business outcomes.
Partner deeply with other ads product teams as an embedded collaborator, ensuring recommendations and incentives are tightly integrated with AM workflows, Salesforce data infrastructure, and marketplace intelligence.
Work cross-functionally with Measurement, Ranking, Targeting, Data Science, and Engineering to build scalable, high-quality recommendation logic that performs across advertiser tiers.
Partner with Sales and Account Management to surface operational insights, identify opportunity gaps, and ensure recommendations translate to real advertiser outcomes.
Leverage A/B testing, experimentation, and data analysis to evaluate recommendation quality, drive continuous improvement, and communicate results clearly across a matrixed organization.
Engage regularly with advertisers and customer support to understand friction points, validate recommendation relevance, and identify new opportunity areas.