> Markdown version of [/jobs/ext/3571327-director-data-science-new-revenue-bets](https://www.wearedevelopers.com/jobs/ext/3571327-director-data-science-new-revenue-bets). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Director, Data Science - New Revenue Bets - **Company:** The Meta Game, Inc. - **Location:** San Francisco, CA, United States - **Salary:** $253,000.0 - $314,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Computer Engineering, Data Infrastructure, Apache Hive, Software Product Management, Prompt Engineering, Apache Spark, Data Strategy, Information Technology, Machine Learning Operations, Presto, Virtual Agents - **Published:** October 3, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=c6b2fc987f56ca6c ## About the Role * 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, * 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 ## Description * 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