Product Manager, YouTube Recommendations, Algorithmic Understanding and Regulation
Minimum qualifications: ? Bachelor's degree or equivalent practical experience. ? 3 years of experience in product management or related technical role. ? 1 year of experience taking technical consumer products from conception to launch. ? Experience with data analysis including SQL and analysis tools.
Preferred qualifications: ? Master's degree or PhD in a technology or quantitative field. ? 2 years of experience in a role preparing and delivering technical presentations to leadership. ? 2 years of experience working cross-functionally with engineering, UX/UI, sales, finance, and other stakeholders. ? 2 years of experience working in regulatory environments. ? Experience in an analysis role including data science, strategy, or other analytical roles. ? Experience working on recommendation systems or other machine learning systems.
About the job
At Google, we put our users first. The world is always changing, so we need Product Managers who are continuously adapting and excited to work on products that affect millions of people every day.
In this role, you will work cross-functionally to guide products from conception to launch by connecting the technical and business worlds. You can break down complex problems into steps that drive product development.
One of the many reasons Google consistently brings innovative, world-changing products to market is because of the collaborative work we do in Product Management. Our team works closely with creative engineers, designers, marketers, etc. to help design and develop technologies that improve access to the world's information. We're responsible for guiding products throughout the execution cycle, focusing specifically on analyzing, positioning, packaging, promoting, and tailoring our solutions to our users.
The YouTube Discovery Product Management team is responsible for Home feed, personalized recommendations, and more. The team collaborates with research and engineering to manage the machine learning systems that determine which content viewers see. The team is responsible for increasing daily active users and time spent, pioneering innovation in machine learning and recommendation systems, enhancing the viewer experience beyond engagement metrics, while upholding responsibility to viewers, creators, and society.
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 $122,000-$178,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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
? Work with engineering and data science to develop new analysis tools and improve existing analysis tools to better understand the algorithm and opportunities for improvement.
? Develop new metrics to measure success and work with the team to implement these metrics.
? Work cross-functionally across engineering, UX, legal, and privacy to help evolve data and privacy strategy for how we collect and store user data along with the surrounding experience.
? Help navigate regulatory inquiries around the algorithm and user data.
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