Alphabet · San Francisco, CA

Social Intelligence Manager, Brand Social

San Francisco, CA, USA +1 moreManager or leadMarketing

Listed on Alphabet’s official careers site. Listed as of October 30, 2026. Check that it is still open and apply there.

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Job description

info_outline About the job In this role, you connect social signals to human behavior, distinguish meaningful shifts from momentary noise, and turn those community insights into clear, actionable direction for marketing, creative and product teams. You live in social conversation daily, helping us manage issues and opportunities as they arise, while driving marketing’s larger understanding of cultural shifts. As Brand Social’s in-house social anthropologist, you will investigate emerging online communities, subcultures, and platform behaviors to explain the "why" behind the data.

You will also lead day-to-day operations of the global, 24/7 listening program, directing agency and vendor partners. You will oversee systems for monitoring, triage and real-time community engagement, for cultural moments, positive mentions, brand safety issues, and emerging risks. Working with internal and external partners, you will leverage AI and automation to scale our listening systems, using signals to inform long-term product roadmaps, brand marketing and daily channel automation briefs, improve listening systems and cross-functional processes through AI and automation.

You will investigate what positive and negative signals reveal about recurring needs, friction, workarounds, and unexpected uses, working with product partners to assess implications and inform decisions. You will further be highly involved in Google’s brand channel programming priorities, including by inputting into the strategic direction of owned social media channels and informing content, campaign and channel briefs.

You will combine analytical excellence with strong storytelling, cultural curiosity, and operational leadership. You are fascinated by people and communities, understand how platform mechanics shape participation and distribution, and can distinguish a supported finding from an interpretation that needs further investigation.

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