Director, Data Science - New Revenue Bets
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5,686 recent H-1B filings · 1 similar-role filing
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742 recent certified PERM filings · 107 similar-role filings
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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.
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
Minimum Qualifications
- 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
Preferred Qualifications
- 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
Sponsorship evidence
Why Openbound reached the conclusions above.
Visa sponsorship evidence
Current posting
Silent on sponsorship
Employer H-1B history
- 5,686
- recent certified H-1B filings
- 3,007
- new-hire petitions
- 1
- filings for similar roles
- 5,150
- so far in FY2026
Filed titles like this role: data science director
More evidence details
- 1 certified H-1B filing for this same role
- 5,686 recent certified H-1B filings across the employer
- Still filing this year — 5,150 filings in FY2026
- 2,778 USCIS H-1B new-employment approvals, counted separately from LCA filings
- Strong filing activity in CA
- 11,582 further USCIS approvals for extensions or transfers
- The posting says nothing about sponsorship either way
Strong filing activity in CA.
Green card sponsorship evidence
Employer PERM history
- 742
- recent certified PERM filings
- 107
- filings for similar roles
- 478
- filings in this location
Filing history reflects past employer behavior; it isn't a promise for this opening.
All open roles at MetaHow Openbound evaluates sponsorship
Visa history uses official U.S. Department of Labor H-1B LCA disclosure data and USCIS H-1B petition history. Green card history uses DOL PERM disclosure data. Each is read for the employer as a whole, for roles like this one, and for this location, weighted toward the most recent fiscal years.
An employer is matched to its filing entities by verified legal name and reviewed aliases; a match is never made on a name resemblance alone. Where no verified entity can be matched, the page says so and draws no conclusion from the absence. 1,277 filing titles were examined for this employer.
What this posting states outranks history in both directions, and an employer's published policy outranks past filings. Filing history reflects past behavior; it is not a promise of sponsorship for this opening, and none of this is legal advice.