Google

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

Google San Bruno, California, United States · $138K–$197K/yr

Software Development · 10,001+ employees

Oct 22
data-scientist Mid (2-5 yrs) Full-time United States
Create a free account to apply — email only, no card. You can also save this posting or score it against your profile with AI.

About the role

Develop and maintain advanced forecasting models to project global ad revenue trajectories while partnering with cross-functional teams to analyze business growth drivers. Design scalable data pipelines and executive dashboards to translate complex datasets into actionable strategic recommendations for leadership.

What they look for

Python R SQL Statistical Analysis Financial Modeling Data Science Forecasting Business Intelligence Data Pipelines Dashboard Creation Quantitative Analysis Strategic Planning Communication Presentation Skills Problem Solving

Requirements

Requires a Master's degree in a quantitative discipline and at least 3 years of experience in analytics, coding, and statistical modeling. Candidates must possess strong technical abilities in SQL, Python, or R and the communication skills to present insights to executive audiences.

Benefits

Bonus Equity Health Insurance

Full description

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.

About the job:

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.

Similar roles