> Markdown version of [/jobs/ext/2034856-ic8-data-scientist-product-analytics-cp-new-revenue-bets](https://www.wearedevelopers.com/jobs/ext/2034856-ic8-data-scientist-product-analytics-cp-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). --- # IC8 Data Scientist, Product Analytics - CP New Revenue Bets - **Company:** The Meta Game, Inc. - **Location:** Menlo Park, CA, United States - **Salary:** $253,000.0 - $314,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Infrastructure, Apache Hive, Software Product Management, Usage Analysis, Apache Spark, Data Strategy, Machine Learning Operations, Presto, Virtual Agents - **Published:** August 12, 2026 - **Apply:** https://www.nexxt.com/job.asp?id=3350877223&tx=FL131FFK&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role 1. 12+ years of experience in data science, analytics, or a quantitative field 2. Demonstrated company-wide influence, cross-org strategy, and sustained execution on high-complexity problems 3. Proven ability to context-switch across disparate problem domains (growth, monetization, international expansion, AI products) while maintaining high-quality output 4. Track record of setting direction on company-critical problems and influencing cross-org strategy 5. Experience thriving in multi-team, multi-stakeholder environments with the ability to build trust quickly and drive outcomes through influence 6. Comfort operating in early-stage, high-ambiguity environments where metrics, frameworks, and questions haven't been defined yet 7. Ability to synthesize complex analysis into clear narratives for VP+ and cross-functional leadership, 1. Familiarity with Meta's data infrastructure (large-scale data querying tools (e.g., Hive, Presto, Spark), experimentation platforms, and ML infrastructure) 2. Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies 3. Experience in subscription/recurring-revenue businesses (LTV modeling, retention analytics, pricing strategy) 4. Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) 5. Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) 6. Background in AI product measurement or AI agent evaluation frameworks 7. International/APAC market analytics experience - understanding regional dynamics, localization challenges, and cross-market comparisons 8. Prior experience operating as a principal-level IC embedded in a leadership team across multiple concurrent bets ## Description 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., 1. Provide senior analytical leadership across New Revenue Bets workstreams - Subscriptions, BizAI, and XF APAC - where it's most needed at any given moment 2. Work directly with VPs and senior cross-functional leaders across the company 3. synthesize complex analysis into actionable insights for executive audiences and shape investment decisions at the highest levels 4. Define measurement frameworks and success metrics for nascent revenue products where playbooks don't yet exist 5. make ambiguity tractable for emerging business models 6. Drive analytical insights on subscriber growth, retention, LTV modeling, pricing/packaging strategy, and product-market fit for Meta's subscription offerings 7. 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 8. Lead cross-functional analytics supporting APAC market expansion - localization insights, regional product-market dynamics, and go-to-market measurement 9. Serve as a unifying analytical voice across multiple teams and workstreams 10. identify shared challenges, propagate learnings, and ensure teams are building on each other's work 11. Establish best practices in measurement, experimentation, and causal inference for early-stage revenue products 12. propagate learnings across the org and beyond 13. Elevate the craft and impact of other ICs and managers through coaching, collaboration, and exemplar work 14. Redesign analytical workflows to leverage AI/ML tools and agents at scale 15. model how ICs should integrate AI as a force multiplier ## Related Videos - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Data: The Deciding Factor in AI Success](https://www.wearedevelopers.com/videos/100310-data-the-deciding-factor-in-ai-success) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Let's Get Aggregated: Custom UDAFs in Spark ](https://www.wearedevelopers.com/videos/1649-let-s-get-aggregated-custom-udafs-in-spark) - [AI PowerPlay: Building High-Impact Teams & Transformative Solutions](https://www.wearedevelopers.com/videos/1005-ai-powerplay-building-high-impact-teams-transformative-solutions) - [Building the platform for providing ML predictions based on real-time player activity](https://www.wearedevelopers.com/videos/944-building-the-platform-for-providing-ml-predictions-based-on-real-time-player-activity) ## Related Articles - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)