Manager, Strategy and Operations Analytics, YouTube Ads GTM

As a part of the YouTube Ads GTM Strategy and Operations team, you will bridge the gap between YouTube Ads product/engineering teams and the global commercial organization. In this role, you will lead a team of analysts to drive operational excellence and deliver impactful insights that support the YouTube Ads business plan. You will serve as the technical anchor for the team, establishing a steady operational rhythm and transitioning from reactive data requests to proactive strategic initiatives, including AI-driven self-service analytics and complex data triangulation architecture.At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we 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 cutting-edge 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.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $186000 - $270000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Minimum qualifications:

• Bachelor's degree in Mathematics, Engineering, Computer Science, a quantitative field, or equivalent practical experience.
• 8 years of experience in management consulting, sales operations, business strategy, investment banking, venture capital, private equity, or corporate advisory, or 6 years of experience with an advanced degree.
• Experience with data analysis, statistical analysis, data pipelines (e.g., SQL), and dashboard solutions.
• Experience directly managing and leading a team of analytics professionals.
• Experience with statistical modeling techniques and programming languages (e.g., Python or R) for data analysis.

Preferred qualifications:

• Experience building data triangulation architecture to connect isolated data streams into a unified business view.
• Experience with advanced causal inference techniques, including incrementality measurement, observational studies, and attribution modeling.
• Experience working with sales or go-to-market teams in a global organization.
• Experience navigating business issues and shaping strategy in a fast-moving organization.
• Experience acting as a technical mentor in data science, guiding junior analysts and fostering a high-performing culture.