Senior / Principal Data Scientist - Discovery

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. 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 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. For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. All full-time employees are also eligible for equity compensation and for benefits as described on this page. Annual Salary Range $307,430—$373,680 USD Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted). Roblox provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability

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.

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.