Meta is seeking a Product Operations Manager to support the Central and Standalone Products organization, driving operational excellence, data-informed decision-making, and cross-functional alignment across a portfolio of core Meta products. In this role, you will partner closely with product, engineering, design, and data science teams to identify operational gaps, build scalable processes, and translate complex product and business data into actionable insights. You will play a critical role in ensuring that product teams operate efficiently and that strategic priorities are clearly tracked, communicated, and executed.

Responsibilities

Partner with product and engineering teams across Central and Standalone Products to identify operational inefficiencies and design scalable solutions that improve team velocity and product quality
• Build and maintain dashboards, reporting frameworks, and metrics systems that provide visibility into product health, launch readiness, and key performance indicators
• Conduct structured data analysis using SQL and business intelligence tools to surface trends, diagnose issues, and inform product and operational decisions
• Define and manage operational rhythms including planning cycles, cross-functional syncs, and progress tracking mechanisms for the product portfolio
• Translate ambiguous business and product questions into well-scoped analytical workstreams with clear outputs and stakeholder-ready deliverables
• Collaborate with cross-functional partners in data science, finance, and operations to align on shared metrics definitions and reporting standards
• Support product launch operations by coordinating readiness reviews, tracking dependencies, and communicating status to relevant stakeholders
• Develop written materials including executive summaries, operational reviews, and strategic briefs that communicate product performance and operational priorities
• Identify opportunities to automate manual workflows and reporting processes, leveraging available tooling to reduce operational overhead
• Contribute to team-level planning by synthesizing input from multiple product areas and helping prioritize initiatives based on impact and feasibility

Minimum Qualifications
• Currently has, or is in the process of obtaining a Bachelor's degree in a directly related field, or equivalent practical experience. Degree must be completed prior to joining Meta
• 2+ years of experience in product operations, business operations, strategy, or a related analytical function
• Experience using SQL to extract, manipulate, and analyze large datasets to answer business and product questions
• Experience building dashboards or reporting frameworks using business intelligence tools to track product or operational metrics
• Experience managing cross-functional projects and communicating progress and findings to stakeholders across product, engineering, and business functions
• Experience breaking down ambiguous problems into structured analytical frameworks and delivering actionable recommendations

Preferred Qualifications
• 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)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience supporting a portfolio of multiple products or product lines simultaneously within a large technology organization
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Familiarity with product development lifecycles and experience coordinating operational processes around product launches or roadmap planning
• Experience with Python or other scripting languages for data analysis or workflow automation
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience designing or improving operational processes in a fast-paced, cross-functional environment with multiple competing priorities