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Group Social Science and Central Marketing Services Manager
Group Social Science and Central Marketing Services Manager-April 2024
San Francisco
Apr 28, 2025
ABOUT GOOGLE
Our mission is to organize the world’s information and make it universally accessible and useful.
10,000+ employees
Technology
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About Group Social Science and Central Marketing Services Manager

  Minimum qualifications:

  10 years of experience in social marketing.

  10 years of experience in data analysis.

  Experience with AI, data mining, machine learning, and statistical analysis.

  Experience with social media platforms and how they work.

  Preferred qualifications: Experience working with international teams.

  Ability to work cross-functionally with a high number of stakeholders.

  Ability to produce executive-friendly mass communication.

  High attention to detail, and increasing levels of responsibility and independence.

  About the job

  As the Group Social Science and Central Marketing Services Manager, you will lead a Social Science team and build centralized systems that enable Google marketers to effectively and efficiently market their products and the Google brand. With social analytics at the center, your work will develop the opportunities that come from a deep understanding of the science behind how social platforms, networks, and communities work. This work will include the development of shared frameworks and centralized systems for social-marketing measurement (across paid, owned, and earned), an always-on newsroom to identify relevant trends and develop brand engagement opportunities, influencer identification, and community management.

  In this role, you will use the latest in AI technology to identify deep social insights, finding opportunities to train and apply AI models for ongoing applications of social marketing. You'll drive real-time actionable optimization for increased performance on all social and influencer marketing efforts.

  Know the user. Know the magic. Connect the two. At its core, marketing at Google starts with technology and ends with the user, bringing both together in unconventional ways. Our job is to demonstrate how Google's products solve the world's problems--from the everyday to the epic, from the mundane to the monumental. And we approach marketing in a way that only Google can--changing the game, redefining the medium, making the user the priority, and ultimately, letting the technology speak for itself.

  The US base salary range for this full-time position is $203,000-$299,000 + 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 for new hire 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

  Be an expert on the latest developments in AI models, how they can be applied in social marketing, and how to measure the impact on the business.

  Merge the understanding of social behaviors within social communities with the application of new and custom AI models to advance our understanding of consumer conversation, content generation, and trend identification putting the power in marketers.

  Lead a team (or partners) who can implement the use of AI models (data capture, cleaning, storage, AI application, APIs, UI, etc.).

  Understand the evolution of social platforms to keep our approaches current based on data proving outcomes.

  Rethink how we measure ROI on business objectives and show how Brand and social/influencers impacts our business OKRs from both a direct attribution lens and an incrementality lens, which requires data infrastructure and modeling.

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