IC8 Data Scientist, Product Analytics - CP New Revenue Bets

Meta•Menlo Park, CA

9d•$253,000 - $314,000

About The Position

We're looking for a experienced Data Scientist who can serve as a product analytics leader and strategic generalist across the CP - New Revenue Bets org. This role is designed for someone who combines deep analytical rigor with strong product sense - someone who can step into any pillar (Subscriptions, BizAI, or XF APAC) and quickly add leverage where the team needs it most. You'll operate with significant autonomy, partnering directly with VPs and cross-functional leaders at the most senior levels of company leadership to shape strategy and unblock critical workstreams. You'll be the analytical connective tissue across our pillars - building bridges between teams, synthesizing insights across workstreams, and ensuring our bets are informed by the rigorous data-driven perspective.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
12+ years of experience in data science, analytics, or a quantitative field
Advanced degree (MS/PhD) in Statistics, Economics, Computer Science, or related quantitative discipline
Demonstrated company-wide influence, cross-org strategy, and sustained execution on high-complexity problems
Proven ability to context-switch across disparate problem domains (growth, monetization, international expansion, AI products) while maintaining high-quality output
Track record of setting direction on company-critical problems and influencing cross-org strategy
Experience thriving in multi-team, multi-stakeholder environments with the ability to build trust quickly and drive outcomes through influence
Comfort operating in early-stage, high-ambiguity environments where metrics, frameworks, and questions haven't been defined yet
Ability to synthesize complex analysis into clear narratives for VP+ and cross-functional leadership

Nice To Haves

Familiarity with Meta's data infrastructure (large-scale data querying tools (e.g., Hive, Presto, Spark), experimentation platforms, and ML infrastructure)
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
Experience in subscription/recurring-revenue businesses (LTV modeling, retention analytics, pricing strategy)
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Background in AI product measurement or AI agent evaluation frameworks
International/APAC market analytics experience - understanding regional dynamics, localization challenges, and cross-market comparisons
Prior experience operating as a principal-level IC embedded in a leadership team across multiple concurrent bets

Responsibilities

Provide senior analytical leadership across New Revenue Bets workstreams - Subscriptions, BizAI, and XF APAC - where it's most needed at any given moment
Work directly with VPs and senior cross-functional leaders across the company; synthesize complex analysis into actionable insights for executive audiences and shape investment decisions at the highest levels
Define measurement frameworks and success metrics for nascent revenue products where playbooks don't yet exist; make ambiguity tractable for emerging business models
Drive analytical insights on subscriber growth, retention, LTV modeling, pricing/packaging strategy, and product-market fit for Meta's subscription offerings
Partner on the data strategy for AI-powered business tools - measurement of AI agent effectiveness, ROI frameworks for business customers, and opportunity sizing for new capabilities
Lead cross-functional analytics supporting APAC market expansion - localization insights, regional product-market dynamics, and go-to-market measurement
Serve as a unifying analytical voice across multiple teams and workstreams; identify shared challenges, propagate learnings, and ensure teams are building on each other's work
Establish best practices in measurement, experimentation, and causal inference for early-stage revenue products; propagate learnings across the org and beyond
Elevate the craft and impact of other ICs and managers through coaching, collaboration, and exemplar work
Redesign analytical workflows to leverage AI/ML tools and agents at scale; model how ICs should integrate AI as a force multiplier