Program Manager, Analytics AI, Strategy and Operations, YouTube

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 are a data-driven team that wants to harness the power of AI in ways that can meaningfully improve our ability to analyze and understand data. With AI-augmented analysis, we want to enable faster and better decision making for our leadership.

In this role, you will be building and rolling out AI-enabled investigative solutions across Product Operations (ProdOps) and the entire organization. Your work will be at the confluence of product, engineering, data, analytics, strategy and operations and technology. You will frequently interface with executive leaders across YouTube, and partner closely with cross-functional teams including Data Science, Product Management and Engineering. If you are motivated by the mission of leading through AI-powered problem-solving excellence and transforming how we work, this is a chance to make a profound and lasting impact.

At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we listen, 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.

The US base salary range for this full-time position is $189,000-$274,000 + 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.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Develop AI tools and infrastructure that make analytics more efficient by designing, implementing, and scaling solutions for key investigative and operational workflows.
• Deploy these AI solutions at scale across analytics and product teams at YouTube, from training to leading the adoption (e.g., AI-assisted SQL solutions enabling stakeholders to get answers to simple data questions, vibe coding, Gemini CLI, etc.).
• Lead coordination with other analytics functions to ensure that YouTube teams are focused on using AI in analytics where it can have the most impact.
• Train/mentor the rest of the team in AI by developing and executing change management strategies, establishing a framework for documenting insights, challenges, and successes and advocating upskilling across the organization.

Minimum qualifications:

• Bachelor’s degree in a technical or business field, or equivalent practical.
• 8 years of experience in program management.
• Experience with development in AI, including SQL for data extraction.
• Experience managing operations or product strategy for platforms with a user base of millions/billions, including experience with concurrency systems and global data governance.
• Experience leading technical programs from conception to launch within tech environments.

Preferred qualifications:

• MBA or Master’s degree in Computer Science, Data Science, Engineering, or a quantitative related field.
• Experience in BI tools and the ability to translate complex data sets into actionable executive-level insights, and one scripting language (e.g., Python or AppScript) to automate data analysis.
• Experience in management consulting or internal process consulting, with a focus on organizational effectiveness and process design for large-scale technical teams.
• Familiarity with developing agentic workloads (e.g., AI that reasons, plans, and uses tools) and implementing conversational AI frameworks beyond standard large language model chatbots.