Senior Data Scientist, VRChat

• The ideal candidate will have a background in a technical field, will have experience working with large production data sets, and will have some experience delivering data products on a fast-paced team
• 5+ years of experience in data science, product analytics, data analytics, quantitative analysis, or a related analytical role
• Expert SQL skills and strong proficiency with Python or R for analysis, experimentation, modeling, automation, and reproducible workflows
• Strong product sense, with experience translating ambiguous product or business problems into structured analyses, metrics, experiments, and recommendations
• Experience designing, analyzing, and interpreting experiments, including A/B tests, guardrail metrics, and common statistical pitfalls
• Experience building dashboards, reporting systems, reusable analyses, or data products that help stakeholders self-serve and make better decisions
• Familiarity with AI-assisted analytical workflows, such as using LLMs or agents for code generation, exploratory analysis, documentation, QA, summarization, or workflow automation
• Strong judgment around data quality, statistical validity, reproducibility, privacy, and the limitations of AI-generated analysis
• Excellent communication and stakeholder management skills, including the ability to explain complex findings clearly and influence senior audiences
• Bachelor’s or Master’s degree in a technical, quantitative, or data-related field, or equivalent practical experience

Desirable

• As a Senior Data Scientist on VRChat’s Data Team, you will play a key role in driving strategic product decisions and advancing our product roadmap across growth, user experience, creator, and economy verticals
• Partner with cross-functional teams to define high-impact product questions, success metrics, and decision frameworks
• Analyze user behavior, creator activity, content ecosystems, retention, growth, monetization, and social dynamics to identify opportunities and risks
• Design and analyze experiments, including A/B tests and other causal measurement approaches, to evaluate product launches, campaigns, and strategic initiatives
• Define and improve core product metrics, dashboards, diagnostic views, and recurring reporting that help teams understand what is changing and why
• Build durable analytical assets such as reusable notebooks, data marts, metric definitions, self-serve dashboards, and analysis templates
• Use AI-assisted and agentic workflows to accelerate analysis, automate repetitive investigation, improve documentation, and build lightweight internal tools for common analytical questions
• Collaborate with Data Engineering and product teams to improve data quality, instrumentation, modeling, and source-of-truth definitions
• Communicate findings clearly to technical and non-technical audiences, including senior stakeholders, and influence product decisions through evidence and judgment

• All job offers are subject to satisfactory referencing and background checks