Finance Manager, MSL FP&A

Meta

$150K — $180K *
Finance & Insurance
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 9+ years in FP&A
  • Leadership in large, matrixed organizations
  • Strong data synthesis and analytical skills
  • Ability to manage competing priorities effectively
  • Excellent cross-functional communication abilities
  • Advanced skills in financial modeling and data analysis
  • Experience working independently across time zones

Responsibilities

  • Develop in-depth knowledge of MSL's growth drivers and roadmaps
  • Apply core FP&A principles to budgeting and forecasting
  • Oversee end-to-end financial consolidation and reporting processes
  • Communicate a cohesive MSL narrative in financial materials
  • Act as liaison for budget-related matters across teams
  • Drive initiatives to improve and automate financial processes using AI
  • Support ad-hoc analytics and reporting needs

Benefits

  • High visibility role with significant organizational impact
  • Opportunity to work in a cutting-edge AI environment
  • Collaboration with senior leadership and cross-functional teams
  • Focus on innovation and continuous process improvement
  • Professional development opportunities in AI integration
Full Job Description
We are looking for a Finance Manager to join the Meta Superintelligence Labs (MSL) Finance team. This role will drive the end-to-end consolidation and FP&A operational processes for Meta's MSL spend, working with finance partners, accounting, and corporate finance to deliver accurate, timely financial reporting and forecasting to senior leadership. This is a high-visibility role working on one of the top priority areas for Meta.

Responsibilities

Develop a detailed understanding of the Meta Superintelligence Labs (MSL) org, drivers of MSL growth and roadmaps
• Operate with a deep understanding of core FP&A planning principles, processes, and deliverables such as budgeting, forecasting, annual planning, accruals and close, variance analysis, approvals, and reporting
• Drive quarterly financial consolidations (reporting), annual budget planning, close and forecast processes end to end. Proactively surface timelines, progress, risks and opportunities to the MSL Finance team
• Develop a clear and concise 'MSL' narrative during financial deliverables, stay up to date on business updates and key financial information on an ongoing basis
• Serve as first point of contact and liaison to Corporate finance, Headcount planning, Recruiting, HR and Accounting on matters relating to budgets
• Identify and drive initiatives to continuously improve, automate, and scale forecasting, reporting, and other financial processes for the MSL org using AI tools or foundational data improvements
• Support ad-hoc analytics and reporting

Minimum Qualifications
• 9+ years of experience in FP&A
• Experience leading close and/or forecast processes in a large, matrixed organization
• Strong analytical skills with the ability to synthesize large volumes of financial data into clear narratives for senior leadership
• Ability to prioritize competing workstreams based on close cycle deadlines, impact, and stakeholder needs
• Cross-functional communication skills and ability to drive alignment across teams with competing priorities
• Advanced proficiency in financial modeling and data analysis tools
• Ability to work independently with limited guidance, across multiple time zones with both Finance and key cross functional business partners

Preferred Qualifications
• Experience preparing materials for VP-level or C-suite reviews
• Master's degree in business, finance, accounting, management or related field
• Experience with Financial systems (e.g. Essbase, Oracle Financials), dashboard reporting tools (i.e. Tableau) and SQL
• Experience in supporting an AI lab or technology company with a focus on AI
• 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

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