Senior Data Scientist
New
Work from anywhere! VRChat is a 100% remote companyFull-TimeSenior
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Experience
- 5+ years
- Required Skills
- PythonSQLProduct AnalyticsData modelingA/B testingR
Requirements
- 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.
Responsibilities
- 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.
View Full Description & ApplyYou'll be redirected to the employer's site
