Senior Data Scientist - Consumer Frontend

Senior Data Scientist - Consumer Frontend

San Mateo, CA, United States Data Science & Analytics

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators.

At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.

A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone.

The Data Science & Analytics organization’s mission is to increase our speed, frequency and acumen of making decisions at scale by instilling a data‑influenced approach to building products. We cover a wide area of the data spectrum including analytical data engineering, product analytics, experimentation, causal inference, statistical modelling and machine learning. Aligned and partnering with product groups, we use this vast tool belt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritisation, build data products and measure the impact on our community of players and developers.

Consumer Frontend’s team mission is to deliver the frontend architecture, components, libraries, navigation patterns, and core UI necessary for a high‑quality, performant, intuitive, and observable consumer user experience for gaming and all future use cases. One of the focus areas is UX Excellence through Standardisation, where the goal is to maintain a comprehensive library of high‑quality components and navigation patterns that ensure a consistent and intuitive experience across all consumer surfaces.

As a Data Scientist on the team, you will partner with engineers, product managers, designers, and leaders across the company to shape the future of user navigation, discovery, and interaction across the Roblox app. This includes helping define and evaluate foundational information architecture, navigation systems, and cross‑surface user experiences, while also contributing to the measurement strategy for emerging AI‑enabled workflows that accelerate how user experiences are designed, built, tested, and iterated.

This area is pivotal to Roblox’s long‑term success, directly impacting user engagement, retention, and the overall quality of the consumer experience. You will define KPIs and measurement frameworks for navigation efficiency, content discoverability, user friction, and UX quality, and leverage analytics, experimentation, and statistical rigor to influence product decisions and drive continuous improvements to the usability and effectiveness of the Roblox app.

You Will:

• Define and measure the success of Roblox’s information architecture, navigation systems, and core user experiences. Develop metrics and frameworks that quantify navigation efficiency, information discoverability, user friction, and overall UX quality.
• Develop a deep understanding of user journeys, navigation behaviours, and user intent across the Roblox app. Identify opportunities to improve how users discover content, navigate between surfaces, and accomplish their goals, and translate these insights into product strategy and UX improvements.
• Establish decision‑making frameworks for evaluating trade‑offs across user journeys, surfaces, and product objectives. Help teams understand the downstream effects of navigation and information architecture changes, balancing local optimisations with the health and effectiveness of the broader consumer experience.
• Leverage experimentation, causal inference, and statistical modelling to evaluate platform‑wide initiatives and cross‑surface UX investments. Design rigorous approaches to measurement in environments where traditional experimentation may be…