Business Data Scientist, YouTube Ads, Finance Revenue Analytics and Forecasting

The YouTube Ads Finance team provides strategic, financial, and quantitative guidance across YouTube’s core business generation channels. As a Business Data Scientist on the Revenue Analytics team, you will sit at the intersection of data science, financial forecasting, and product strategy.

In this role, you will design statistical models, build business intelligence frameworks, and translate complex datasets into actionable strategic narratives. Your work will directly inform high-stakes decision-making by YouTube executive leadership, guiding business growth within the YouTube Ads Brand advertising business. This role will drive analysis highlighting how product changes, advertiser behavior, and market economics impact YouTube business, and own business forecasting and reporting for a significant portion of the YouTube Ads business.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $138000 - $197000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Develop, validate, and maintain advanced forecasting models and predictive frameworks to project global ad revenue trajectories.
• Conduct empirical analysis on ad business generation streams to identify growth drivers, advertiser behavior shifts, and yield optimization opportunities.
• Partner cross-functionally with YouTube Product, Engineering, and Global Sales Operations to model the financial impact of platform launches, algorithm updates, and policy shifts.
• Design scalable data pipelines and executive performance dashboards to monitor business health metrics and ecosystem changes.
• Deliver compelling, narrative-driven quantitative presentations to executive leadership, translating complex statistical analyses into concise strategy recommendations.

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.
  

Preferred qualifications:

• 4 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 involving quantitative data analysis related to online advertising and emerging businesses.
• Strong problem solving and technical abilities to drive forecasting, data analysis, and insights for executive audiences (e.g., SQL, R, Python, dashboard creation, advanced financial modeling, statistics, programming), with attention to detail.
• Strong communication skills (e.g., slide decks, live presentations) to distill information concisely to executive audiences.

In most instances, this position requires in-person interviews as part of the hiring process.