Business Data Scientist, YouTube Business Impact Measurement

About the Job

The YouTube Business Go-To-Market team is responsible for driving all go-to-market functions for the YouTube Business Organization, including strategy and business operations, analytics and data science, partnership enablement, and product activation. The team shapes go-to-market priorities to accelerate growth and resource the business accordingly, enhancing skills and capabilities to support execution of business priorities, driving efficiency across business operations, and building excellent go-to-market infrastructure (e.g., data, reports, dashboards). This team combines strategic, operational, and problem-solving skills with a pragmatic sense of how to get things done and drive change across a global organization.

At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we hear, share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun — and we do it all together.

The US base salary range for this full-time position is $138,000-$198,000 + 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

• Design and execute causal studies to address critical business questions.
• Leverage advanced statistical models to find business insights in experimental and observational data.
• Present and communicate actionable insights and recommendations to executives and cross-functional partners.
• Serve as a peer reviewer and consultant for causal studies across the organization.
• Stay current with the latest advancements in causal inference.

Qualifications

Minimum qualifications:

• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
• 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
• Experience using Bayesian Statistics.
• Experience using Causal Inference Analysis.

Preferred qualifications:

• Experience analyzing large language models.