Strategic Data Science Lead, New Revenue Bets

Meta; Little Rock (AR); On-site; USD 253,000 - 314,000; Full time

Job summary

Meta seeks a Director-level Data Scientist to lead analytics for the New Revenue Bets portfolio (Subscriptions, BizAI, XF APAC). You will partner with VPs and senior leaders, drive data-driven strategy, and unify outputs across multiple pillars.

You will build measurement frameworks, model LTV and pricing, guide AI-enabled tooling, and coach ICs and managers to raise the craft of data science across the org.

Qualifications

• Bachelor's degree in CS or related field, or equivalent practical experience.
• 12+ years of experience in data science, analytics, or related quantitative field.
• Advanced degree in a quantitative discipline is preferred.
• Proven company-wide influence and cross-org strategy execution.
• Ability to switch across growth, monetization, international expansion, and AI products.

Responsibilities

• Provide senior analytical leadership across New Revenue Bets workstreams - Subscriptions, BizAI, and XF APAC.
• Work directly with VPs and senior cross-functional leaders across Meta.
• Synthesize complex analysis into actionable insights for executive audiences and shape investment decisions.
• Define measurement frameworks and success metrics for nascent revenue products.
• Lead AI-enabled measurement and opportunity sizing for new capabilities.
• Drive localization insights and regional product-market dynamics for APAC expansion.
• Elevate the craft of other ICs and managers through coaching and collaboration.

Skills

Data science

Analytics leadership

Cross-functional collaboration

Executive communication

Strategic thinking

Education

Bachelor's degree in CS/ML/Math

MS/PhD in Statistics/Economics/CS

Tools

Hive

Presto

Spark

Experimentation platforms

ML infrastructure

Job description

Meta seeks a Director-level Data Scientist to lead analytics for the New Revenue Bets portfolio (Subscriptions, BizAI, XF APAC). You will partner with VPs and senior leaders, drive data-driven strategy, and unify outputs across multiple pillars.

You will build measurement frameworks, model LTV and pricing, guide AI-enabled tooling, and coach ICs and managers to raise the craft of data science across the org.