About the job

We are the analytics team, supporting gTech Users and Products (gUP) team, with key focus on advocating for the user and delivering insights to improve user experience with support and drive a successful product experience.

In this role, you will leverage ML/AI and Data Science to drive a seamless support experience by improving support resources, aligning support with user needs to drive retention, and advocating user pain points to Product Areas (PAs). You will support Knowledge, Information and Core vertical which spans products like Gemini, Search, Maps, Commerce, Assistant etc.

In gTech Users and Products (gUP), our mission is to advocate for Google's users by creating helpful and trusted experiences across the product ecosystem. We achieve this by meeting partners and consumers where they are with support and help, representing their needs with our product partners and proposing fixes and features that elevate their engagement with Google's diverse product ecosystem. Additionally we provide a range of product services that ensure our products are optimized for every user, no matter where they are in the world (e.g., localization, digitization, partner integration and more).
The US base salary range for this full-time position is $127,000-$187,000 + 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 on data modeling, metric development, data prototyping, and insight generation using statistical techniques and machine learning.
  
• Work with engineering, operations, and marketing teams to identify areas to focus effort.
  
• Solve ambiguous problems and discover insights that drive operational, product, and marketing excellence.
  
• Ensure users have excellent product and service experiences.