Senior Data Scientist - Consumer Platforms

WHY DATA SCIENCE & ANALYTICS?

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 modeling 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 craft the product roadmap and prioritization, build data products and measure the impact on our community of players and developers.

WHY Consumer Platforms?

Roblox is used by over 80 million people every day across a wide range of devices, including mobile, desktop, console, and VR. Our users expect exceptional app quality and performance. The Consumer Platform team’s mission is to accelerate Roblox’s growth by launching and platform-specifically optimizing the Roblox experience for every device platform people use to be entertained, connect, and co-experience, making it comparable to best-in-class apps. Collaborating with engineers, product managers, and leaders across the company, you will apply your data science expertise to quantify the causal impact of platform-specific levers - such as content, features, performance, and stability - to craft tailored growth strategies for each platform, delivering an outstanding user experience while maintaining Roblox’s dedication to multi-platform accessibility.

You Will:

• Conduct causal studies to understand how the impact of top growth drivers varies by platform and leverage these insights to craft and optimize platform-specific growth strategies.
• Enhance insight into business outlooks at the platform level and establish platform-specific growth targets by incorporating external market research and competitive analysis.
• Define and measure success metrics for app quality and performance, identifying which app quality and performance levers matter most to users and how they influence engagement and monetization.
• Use A/B experiments and causal inference methods to evaluate the success of feature launches; Increase rigor in the product release process and cultivate the adoption of a performance-driven product development approach.
• Access, transform, and analyze raw data, presenting actionable insights using a custom analytics toolkit built with innovative open-source libraries.
• Operationalize and scale metrics monitoring by developing tools that enable quick data slicing, dicing, and root-cause analysis.
• Navigate ambiguity and collaborate with cross-functional teams across User, Growth, Engine, and Creator organizations to drive impactful platform improvements.

You Have:

• An advanced degree or equivalent experience in Statistics, Applied Math, Physics, Engineering, Computer Science, Economics, or a related quantitative field.
• 5+ years of proven experience in a data science role, ideally with a focus on improving app quality and performance.
• Strong data skills and experience working with large datasets, including telemetry logging, data pipeline development, dashboard design and dashboard implementation.
• Deep knowledge and practical expertise in statistical methods, time series forecasting, causal inference techniques, and experimental design.
• Ability to drive an area as an individual contributor and an inspiring leader.
• Ability to apply creative, first-principles reasoning to take on ambiguous problems.
• Strong communication skills to present analytics results and data storytelling effectively, influencing engineering teams and leaders.

You Are:

• A capable statistician. You understand the value of characterizing data by its distribution. Covariance, Bias, and Conditional Probability are concepts that you rely on every day.
• An expert transforming data with SQL and a scripting language such as Python or R. You’re experienced in automating efforts and crunching massive volumes of data.
• Experienced in developing models to draw insights from data. You use regression, data mining, and other statistical techniques to build new, scalable solutions to solve complicated business problems. You understand when to apply the appropriate methodology to improve impact pragmatically.