Product Activation Incentives Technical Analyst, YouTube

About the Job

The YouTube Business Central Strategy and Operations team is responsible for leading global, cross-functional initiatives to drive the unprecedented growth and health of the YouTube creator and partner ecosystem. Within the broader team goal, the Incentives Strategy and Analytics team is responsible for designing and operationalizing the core product activation system for YouTube's partner managers.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 $126,000-$181,000 + 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

• Design and build predictive models to power product activation recommendations for YouTube product priorities like shopping, fan funding, podcasts, etc.
• Generate useful product activation insights and reporting to inform product Go-to-market (GTM) and program strategy.
• Improve YouTube Business Organization’s central scaled incentives system through design levers like pricing, goals, etc.
• Own problem solving lifecycle from generating hypotheses, analyzing data, distilling insights to communicating recommendations in a structured way.
• Develop and deploy propensity models using Python, integrating them directly into automated data pipelines to scale predictive insights across the YouTube ecosystem, and navigate YouTube's data warehouse to access and work with relevant data using SQL and other query languages.

Qualifications

Minimum qualifications:

• Bachelor’s degree in Engineering, Computer Science, a related technical field, or equivalent practical experience.
• 3 years of experience using Python or similar languages for building, validating, and deploying predictive models (e.g., propensity, classification).
• 3 years of experience with data analysis, relational databases, and SQL.

Preferred qualifications:

• Master’s degree in Data Science, Engineering, Mathematics, Statistics, Economics, Applied Science, or a related field.
• 5 years of experience in the technical analytics space (data science, data engineering, product analyst, business analyst, business intelligence, etc.).
• Experience using Python for the full modeling lifecycle, from feature engineering and model selection to productionalization.
• Experience drawing insights from data sets using SQL to drive both business and technology decisions.