Senior / Principal Data Scientist, Matchmaking Job at Roblox, San Mateo, CA

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  • Roblox
  • San Mateo, CA

Job Description

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 MATCHMAKING?

Every day, millions of players explore immersive worlds created by our global community. Our mission is to optimize these connections at an unprecedented scale — matching each player to the most engaging experience, in real time, across a dynamic global ecosystem. As a Senior/Principal Data Scientist on the Matchmaking team, you'll help shape the future of how our community discovers, connects, and plays together, solving some of the most challenging optimization and systems problems in the industry.

Matchmaking is the foundational system that connects ~100 million daily active users to tens of thousands of experiences across our global platform infrastructure. You'll partner with engineers, infrastructure teams, and product leaders to solve some of the most complex optimization problems in the industry. Your work will span from low-level resource allocation algorithms to high-level capacity planning strategies. You will define KPIs and measure the impact of matchmaking improvements while discovering optimization opportunities through advanced analytics, modeling, and experimentation. This role sits at the intersection of cutting-edge operations research, large-scale systems engineering, and user experience optimization.

You Will:

  • Design and optimize large-scale matching algorithms to connect millions of users with thousands of experiences in real time.
  • Define and track matchmaking performance metrics that directly improve user satisfaction and system efficiency.
  • Build scalable monitoring and analytics systems for continuous evaluation and root cause analysis.
  • Partner with engineering and infrastructure teams to implement high-performance, low-latency matchmaking pipelines.
  • Develop and deploy advanced optimization models using state-of-the-art mathematical frameworks and large-scale telemetry data.
  • Validate and iterate on improvements through rigorous experimentation and causal inference.
  • Collaborate with our developer community to create transparent and customizable matchmaking solutions that empower creators.
  • Influence platform strategy and contribute as a technical thought leader to advance Roblox's global ecosystem.

You Have:

  • Advanced Degree and/or PhD in Operations Research, Computer Science, Statistics, Applied Mathematics, Industrial Engineering, or other related quantitative fields
  • 6+ years of relevant industry experience with marketplace optimization, auction systems, or large-scale matching platforms (e.g., ride-sharing, ad exchanges, trading systems)
  • Strong optimization systems experience including mathematical modeling, solver integration, and production deployment of marketplace or allocation algorithms
  • Demonstrated ability to drive optimization initiatives as an individual contributor and technical thought leader
  • Experience with real-time bidding, dynamic pricing, or resource allocation systems in high-throughput environments
  • Experience collaborating with Infrastructure teams to optimize system performance and resource utilization (a plus)
  • Ability to communicate optimization results and algorithmic insights to influence engineering teams and business stakeholders

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 .

Annual Salary Range

$316,480—$366,350 USD

Roles that are based in our San Mateo, CA Headquarters are in-office Tuesday, Wednesday, and Thursday, with optional in-office 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 status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Roblox also provides reasonable accommodations for all candidates during the interview process.

Job Tags

Full time, Work experience placement, Work at office, Local area, Monday to Friday

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