Scribd
Senior Paid Social Manager
San Francisco · Senior · Contract
Sponsorship not specifiedDetected 176 days ago
Data ScienceData VisualizationA/B TestingStakeholder ManagementMeta AdsPerformance MarketingCollaboration
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odds of building a lasting career here
40Risky
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
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About the role
- We're seeking an experienced Senior Paid Social Manager to join our performance marketing team, focusing on scaling our presence across Meta, TikTok, Reddit, and exploring other emerging social platforms.
- This role will be instrumental in driving user acquisition for our Everand and Fable products through social advertising strategies.
Responsibilities
- Own and optimize paid social advertising budgets across Meta, TikTok, Reddit, and other social platforms for web and mobile app campaigns
- Develop and execute paid social strategies aligned with our growth objectives and brand guidelines
- Build and maintain sophisticated audience targeting frameworks, sustaining results through platform shifts and creative fatigue
- Design and execute structured testing plans across bidding models, creative formats, and audience strategies
- Collaborate with Creative to develop high-performing ad content, influencing briefs with performance data
- Partner with Product and Engineering to identify landing page friction points, propose A/B test hypotheses, and own a CRO testing roadmap across landing pages
- Partner with data science to develop attribution models, incrementality tests, and LTV signaling pipelines
- Own regular analytics and reporting
- Design and execute structured testing plans across bidding models, creative formats, and audience strategies; produce durable test plans and playbooks the team can reuse
- Own regular analytics and reporting; effectively communicate performance, wins, and challenges to stakeholders
Requirements
- 6+ years of experience managing paid social campaigns, with at least 3 years focused on subscription or D2C products
- Proven track record of scaling social advertising spend efficiently while maintaining or improving LTV:CAC
- Deep expertise in Meta Ads Manager, TikTok Ads, and Reddit Ads platforms, including structured testing across bidding, creative, and audience
- Strong understanding of conversion optimization, audience targeting, and creative testing methodologies
- Experience with attribution models and incrementality testing
- Excellent analytical skills with proficiency in data visualization tools
- Track record of cross-functional collaboration and stakeholder management
- Our four products - Scribd®, Slideshare®, Everand™, and Fable - help billions of people across the globe move beyond access and into insight, application, and expertise.
Nice to have
- Experience marketing subscription products or digital content services
- Google Tag Manager experience
- Familiarity with mobile app marketing and app store optimization
- Familiarity and eagerness to work with AI tools
- San Francisco is our highest geographic market in the United States.
- We carefully consider a wide range of factors when determining compensation, including but not limited to experience
- job-related skill sets
- and other business and organizational needs.
Compensation
- At Scribd, Inc., your base pay is one part of your total compensation package and is determined within a range.
Benefits
- Comprehensive health, dental, and vision coverage
- Mental health support and disability coverage
- Generous paid time off, including vacation, sick time, holidays, winter break, volunteer time, and sabbaticals
- Paid parental leave and family support benefits
- Retirement matching and employee equity
- Learning and development programs and professional growth opportunities
- Wellness and home office stipends
- Lead learning reviews and document test results so insights are actionable and built into future planning cycles
- Scribd Flex (flexible work model)
This listing is sourced directly from Scribd's careers page and normalized into a canonical job model.