Research Data Scientist, YouTube Creator

Minimum qualifications:

• Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
  
• 3 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
  

Preferred qualifications:

• 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
  

About the job:

YouTube Data Science team influences and informs YouTube’s product and engineering leadership. We have a long history of working on projects that are at the heart of the business and have a seat at the table when it comes to the decisions that drive YouTube's continued success. Our mission statement? Improving decisions at YouTube with science.

The focus of the Creator Data Science team is to understand the growth and behavior of YouTube's creator ecosystem from traditional media companies to individual creators who are just getting started, and build tools, systems, and policies that help creators grow on the platform. In this role, you will be involved in collaborations across the Creator organization and format teams (e.g., Shorts, Live) as we build a holistic understanding of the creator ecosystem and business generation.

The US base salary range for this full-time position is $147,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Responsibilities:

• Work with the engineering and product teams to create new metrics, maintain classifiers, enable insights, and drive data-driven decision making.
• Work with data sets and solve investigative issues to understand how brand agreement performs and the impact of new features.
• Conduct end-to-end analysis, including data gathering and requirements specification, processing, analysis, ongoing deliverables and presentations.
• Make business recommendations with effective presentations of findings at multiple levels of stakeholders through visual displays of quantitative information.
• Support launch decisions through experimental design and analysis.