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# Data Scientist - Discovery

- **Company:** Roblox
- **Location:** San Mateo, CA, United States
- **Experience:** Expert
- **Salary:** $307,430.0
- **Contract:** Permanent contract
- **Skills:** Airflow, Complex Networks, Data Warehousing, R (Programming Language), Apache Hive, Python (Programming Language), Machine Learning, Recommender Systems, SQL Databases, Apache Spark, Deep Learning, Roblox
- **Published:** August 25, 2026
- **Apply:** https://www.dice.com/job-detail/bd3e9c7d-be8a-41fc-aa63-3917af26b72f

## About the Role

* 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 Ucontent 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 todesign sophisticated experiments that account for the nuances of a two-sided marketplace and social network effects.
 * Ability todistill high-dimensional problems into succinct, actionable narratives for non-technical executive audiences.

## Description

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 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 Ucontent.


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