> Markdown version of [/jobs/ext/2218105-data-scientist-consumer-apps](https://www.wearedevelopers.com/jobs/ext/2218105-data-scientist-consumer-apps). 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). --- # Data Scientist, Consumer Apps - **Company:** Roblox - **Location:** San Mateo, CA, United States - **Experience:** Expert - **Salary:** $263,670.0 - $322,820.0 - **Contract:** Permanent contract - **Skills:** A/B Testing, Airflow, Big Data, R (Programming Language), Human-Computer Interaction, Python (Programming Language), SQL Databases, Workflow Management Systems, Apache Spark, Information Technology, Roblox - **Published:** August 25, 2026 - **Apply:** https://careers.roblox.com/jobs/8127054?gh_jid=8127054 ## About the Role * An advanced degree in Statistics, Applied Mathematics, Physics, Engineering, Computer Science, Economics, or a related quantitative field. * 8+ years of industry experience in Data Science or a related quantitative discipline, preferably working on consumer-facing products or applications. * Strong analytical and technical skills, with proficiency in Python or R, SQL, and large-scale data processing and workflow tools such as Spark and Airflow. * Deep expertise in statistical analysis, causal inference, experimentation, and measurement methodologies, with a track record of applying these techniques to shape product strategy and drive business outcomes. * Demonstrated ability to independently lead ambiguous, high-impact problem spaces, applying first-principles thinking to develop novel frameworks, approaches, and solutions. * Proven ability to influence across Product, Engineering, Design, Data Science, and leadership, shaping strategy, prioritizing investments, and driving alignment across organizational boundaries. * Exceptional communication and storytelling skills, with the ability to distill complex, high-dimensional problems into clear insights and actionable recommendations for both technical and executive audiences. ## Description Roblox is used by tens of millions of people every day across a wide range of devices, including mobile, desktop, console, TV, and VR. The Consumer Apps team owns the app foundation that makes Roblox feel fast, fluid, and reliable for players and is dedicated to delivering superior performance, reliability, and user experience across all platforms Roblox supports. This team ensures a seamless and engaging user interface that facilitates intuitive interactions while enabling efficient, high-quality experiences across devices. Innovation is at the core of our work, as we continuously enhance features and integrate cutting-edge technologies to solve complex problems. As a Data Scientist on the team, you will help accelerate Roblox's growth by shaping how we launch and optimize Roblox across the diverse device ecosystems where people connect, play, and co-experience. You will partner with Mobile, Desktop, Console, and emerging-platform teams to identify opportunities and develop platform-specific strategies that make Roblox feel best-in-class on every device. You will use data to guide investments across platform expansion, platform-specific product experiences, and ecosystem partnerships. You will develop measurement and experimentation frameworks to understand both the direct and broader ecosystem impact of these investments, helping teams identify growth opportunities, make informed tradeoffs, and continuously improve the Roblox experience while expanding universal access. You Will: * Identify high-potential platform levers and apply causal methods to understand their impact on user behavior, engagement, monetization, and other topline outcomes, translating these insights into platform-specific strategies. * Develop deep expertise in the unique dynamics of each platform - including how the product is experienced, how user cohorts differ, and what drives their behavior - and proactively bring this perspective to broader research and cross-functional decision-making to identify opportunities and explain differences in product and business outcomes. * Build visibility into platform-level business performance and establish growth targets informed by internal data, market research, and competitive insights. * Design and analyze experiments to evaluate product launches, inform iteration, and drive rigorous, data-informed product decisions. * Advance how we measure product impact by developing innovative measurement and causal inference approaches where traditional A/B testing is not feasible, expanding the range of platform investments we can evaluate with rigor and confidence. * Elevate data and experimentation rigor across the broader team by building scalable frameworks and practices around experiment design, success metrics, launch criteria, and launch readiness - helping teams launch confidently and consistently. * Build scalable monitoring and diagnostic capabilities that enable teams to quickly identify trends, investigate changes, and understand root causes. * Partner across Data Science, Product, and Engineering - including Growth, Discovery, Social, and other product areas - to connect insights across surfaces, understand how platform and product changes affect the broader ecosystem, and translate complex data into actionable recommendations that shape strategy and drive impactful platform improvements. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [How Data is Shaping our Games](https://www.wearedevelopers.com/videos/176-how-data-is-shaping-our-games) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [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) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Résumé-Driven Development: How IT trends affect the job market for software developers](https://www.wearedevelopers.com/magazine/59-resume-driven-development-how-it-trends-affect-the-job-market-for-software-developers)