Product Manager II, Display Ads, Audiences
- Mountain View, California
- Onsite
- full time
- $163k–$236k/year
- Posted yesterday
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About the role
MINIMUM QUALIFICATIONS:
* Bachelor's degree or equivalent practical experience.
* 5 years of experience in product management or a related technical role.
* 2 years of experience taking technical products from conception to launch
(e.g., ideation to execution, end-to-end, 0 to 1, etc.).
* Experience working in the Ads industry.
PREFERRED QUALIFICATIONS:
* 3 years of experience in a business function or role (e.g., marketing,
business operations, consulting).
* 2 years of experience working cross-functionally with engineering, UX/UI,
sales finance, and other stakeholders.
* Experience working with remarketing, ads targeting, or privacy enhancing
technologies.
* Excellent entrepreneurial drive and passion for innovation.
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.
Google Display Ads (GDA) is a business that powers the free and open web,
enabling advertisers to reach customers beyond Google’s owned inventory to
connect with the global internet population across millions of third-party
websites, videos, and apps. We help advertisers drive brand awareness, website
traffic, lead generation, and online sales as the largest ad network across web
and apps. GDA also helps publishers create organic content for the Search and
Gemini AI overview business.
Google Ads is at the forefront of AI innovation, applying cutting-edge machine
learning and Generative AI models like Gemini to power a multi-billion dollar
global business.
Our work directly impacts billions of users by protecting users from harm,
improving ad quality, and optimizing campaigns for advertiser
return-on-investment. We foster a culture of deep collaboration, partnering
closely with teams like Google Research and DeepMind to solve complex
challenges. Join us to work on state-of-the-art AI, take on problems at an
unparalleled scale, and build the next generation of advertising technology.
Individual pay is determined by factors including job-related skills,
experience, and relevant education or training.
US: $163000 - $236000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google
[https://www.google.com/about/careers/applications/benefits/].
RESPONSIBILITIES:
* Lead remarketing efforts across Google Display Ads, including web and
app-based user journeys, via tag-based and tagless remarketing lists, and
uploaded customer lists.
* Define a multi-year roadmap to revitalize and expand remarketing across all
serving and identity spaces, and across multiple product clusters and
advertisers.
* Develop new privacy-preserving recovery mechanisms for remarketing, including
IP-based and PII-based solutions that use on-device or TEE-based computing.
* Own dynamic remarketing performance, optimizing for fill rate, product
coverage, and more personalized product selection for feeds-based
advertisers.
* Drive automated signals collection to seamlessly gather additional
remarketing and user/product information for product offerings.
Skills
- Product Management
- Display Ads
- Remarketing
- Ads Targeting
- Privacy Enhancing Technologies
- Machine Learning
- Generative AI
- Product Roadmap
- Cross-functional Collaboration
- Data Analysis
- Technical Product Development
- User Experience
- Stakeholder Management
- Entrepreneurial Drive
- Innovation
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