Product Manager II

MINIMUM QUALIFICATIONS: * Bachelor's degree in Statistics, Physics, Economics, Robotics, Math, a related technical field, or equivalent practical experience. * 5 years of experience in product management or 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). * 1 year of experience building ads algorithm products. * Experience integrating generative AI tools or LLM interfaces into workflows. PREFERRED QUALIFICATIONS: * Master's degree in a technology or business related field. * 3 years of experience in a business function or role (e.g., marketing, business operations, consulting). * 3 years of experience in a role preparing and delivering technical presentations to executive leadership. * 2 years of experience in software development or engineering. * 2 years of experience working cross-functionally with engineering, UX/UI, sales finance, and other stakeholders. * 1 year of experience in technical leadership. 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 Bidding team is focused on building and growing adoption of the next generation of bidding products to drive value to all types of advertisers (all sizes, verticals, levels of sophistication, etc). This includes managing the Search and Shopping Bidding systems (ML, optimization systems, new bid strategies and algorithms, data systems, and platforms) and launching both advertiser-facing bidding products and backend improvements. In this role, you will work on building new algorithms and optimization layers, coming up with new product paths to pursue to drive more advertiser value, and go to market with new suites of ads product features. 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: * Work with partner teams (e.g., engineers, PgMs, UX) during product design and development to implement the requirements to turn PRDs into OKRs for one or more teams. * Analyze the ads system to find new areas of opportunity for both advertiser-facing and backend algorithm product improvements. * Develop new bidding approaches to drive more advertiser value across existing and future bidding strategies. * Work closely with engineering and data science to further optimize the bidding system. * Find opportunities for more advertiser value and business growth within overlapping systems (budget pacing, targeting, auctions) and bidding.