Business Operations Manager, Ads Sales

Meta

$150K — $180K *
Business Services
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 9+ years of experience in business strategy, finance, analytics, consulting, or planning
  • BA/BS in a quantitative field or equivalent experience
  • Proficiency in data analytics, visualization, and scenario-based analysis
  • Experience leading cross-functional projects with executive stakeholders
  • Experience with digital advertising platforms, particularly for small and medium-sized businesses (preferred)
  • Capable of driving initiatives from definition to execution (preferred)
  • Ongoing development and integration of AI tools and practices (preferred)

Responsibilities

  • Develop understanding of the Small and Medium Business Group go-to-market strategy
  • Provide financial leadership across planning cycles including long-range plans and budgets
  • Create ROI and impact frameworks to optimize resource allocation
  • Craft data-driven narratives to influence executive decision-making
  • Establish partnerships with leaders across various business functions
  • Implement scalable financial processes for enhanced efficiency

Benefits

  • Opportunity to shape Meta's business strategy
  • Significant responsibility and direct interaction with product and business leaders
  • Contribute to a rapidly evolving business environment
  • Collaborative cross-functional engagement
  • Access to continuous professional development and AI skill enhancement
Full Job Description
This role requires strategic thinking, influencing stakeholders through written proposals, data-driven presentations, and cross-functional alignment, an analytical mindset, and a bias towards action. You will be challenged to understand and contribute to rapidly changing business models, drive collaboration across teams, develop recommendations on strategic investment decisions, craft annual and long-term plans, and partner with leaders to solve problems and achieve goals. In this role, you will take on significant responsibility, work directly with product and business leaders, and contribute to decisions that shape Meta's business strategy.

Responsibilities

Develop a solid quantitative and qualitative understanding of Meta's Small and Medium Business Group go-to-market strategy
• Provide financial leadership across company-wide planning cycles: long-range plan (LRP), annual budget, and half-year roadmapping
• Develop nuanced ROI and impact frameworks across headcount, expenses, and other investments that will influence key decision makers to allocate resources more efficiently
• Create and socialize data-driven narratives and influence outcomes and decisions at the executive level
• Establish strategic partnerships with leaders of all levels and functions across various business functions
• Help define and implement scalable financial processes to make us and our business partners more efficient

Minimum Qualifications
• 9+ years of experience in business strategy, finance, analytics, consulting, or planning
• BA/BS in a quantitative field (data science, computer science, economics, finance, etc.) or an equivalent degree/experience
• Experience in data analytics, data visualization, and scenario-based analysis
• Experience leading cross-functional projects with executive stakeholders

Preferred Qualifications
• Experience supporting advertising sales organizations, with familiarity in how small and medium-sized businesses engage with digital advertising platforms
• Experience independently scoping and driving cross-functional initiatives from problem definition through to execution
• Experience working in a complex, fast-paced environment or in a high-growth company
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)

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