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 verticals, we use this extensive tool belt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products and measure impact on our community of players and developers.

WHY DISCOVERY EXPERIENCES? 

Roblox is not just a platform; it is a complex, two-sided marketplace where millions of creators meet over 70 million daily active users. The Discovery Experiences team is the technical heartbeat of this ecosystem. We own the surfaces—Home, Search, Matchmaking, and Notifications—that determine how users navigate the metaverse.

As a Principal Data Scientist, you will own the ranking initiatives that power these canvases. You aren't just building models; you are building the economic and social frameworks that decide which experiences thrive. You will report directly to the Senior Director of Data Science and serve as a high-visibility IC leader driving the roadmap for our most critical consumer touchpoints.

You Will:

• Algorithmic Vision: Lead the development of ML solutions and ranking frameworks that power our discovery canvases. You will move beyond local optimizations to solve for long-term ecosystem health and user retention.
• Strategic XFN Partnership: Act as the primary scientific advisor to Product and Engineering leaders. You will use data to inform, drive, and accelerate innovations via deep-dive insights and ML prototypes.
• Causal Inference & Experimentation: Leverage advanced causal inference methodologies to measure the effectiveness of platform initiatives (e.g., social features or site-wide events) that are often susceptible to complex network effects.
• Foundational Scaling: Develop frameworks to scale the hypothesis generation process, ensuring that our experimentation velocity matches our massive growth.
• First-Principles Problem Solving: Apply creative, first-principles reasoning to ambiguous problems, such as balancing the visibility of established "top tier" experiences with the discovery of new, niche UGC content.

You Have: 

• Advanced degree (Masters or PhD) in a quantitative field (Statistics, CS, Physics, Applied Math, or Economics).
• 10+ years of experience (or 6+ with a PhD) in Data Science, Economics, or ML Engineering, specifically within large-scale recommendation systems or UGC content platforms.
• Expert in the modern data stack (Python, R, SQL, Hive, Spark, Airflow) and have a deep theoretical and practical understanding of Deep Learning.
• Ability to design sophisticated experiments that account for the nuances of a two-sided marketplace and social network effects.
• Ability to distill high-dimensional problems into succinct, actionable narratives for non-technical executive audiences.