Meta
Director, Data Science - New Revenue Bets
$253K–$314K
Sunnyvale, CA +6 · Remote · Director · Full-time · Posted Jun 11, 2026
- Location
- Sunnyvale, CA
Bellevue, WA
Menlo Park, CA
Seattle, WA
New York, NY
San Francisco, CA
Remote, US - Experience
- 12+ years in data science, analytics, or a quantitative field.
- Education
- Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience; advanced degree (MS/PhD) in Statistics, Economics, Computer Science, or a related quantitative discipline.
About the job
Leads product analytics and measurement across Meta’s New Revenue Bets, shaping strategy and investment decisions for subscription products, AI-powered business tools, and APAC expansion.
What you'll do
- Provide analytical leadership across workstreams and translate complex analysis into executive insights that inform strategy and investment.
- Define measurement frameworks and analyze subscription growth, retention, LTV, AI-tool effectiveness, and APAC market expansion.
- Set measurement and experimentation practices, coach colleagues, and redesign analytical workflows using AI/ML tools and agents.
What they ask for
- Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
- 12+ years of experience in data science, analytics, or a quantitative field.
- Demonstrated company-wide influence, cross-org strategy, and sustained execution on high-complexity problems.
- Ability to synthesize complex analysis for VP+ audiences and operate across ambiguous, multi-team environments.
Nice to have
- Advanced degree (MS/PhD) in Statistics, Economics, Computer Science, or a related quantitative discipline.
- Experience in subscription businesses, AI product measurement, responsible AI, or international/APAC market analytics.
Pay
$253,000/year to $314,000/year (base salary)
Tools
Hive, Presto, Spark, experimentation platforms, ML infrastructure, prompt/context engineering, agent orchestration
AI focus
Measure AI agent effectiveness and customer ROI, evaluate AI products, apply responsible AI practices, and redesign analytical workflows using AI/ML tools and agents.
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