Product Data Scientist, Android Onboarding and Settings

Android is Google’s mobile operating system powering more than 3 billion devices worldwide. Android is about bringing computing to everyone in the world. We believe computing is a super power for good, enabling access to information, economic opportunity, productivity, connectivity between friends and family and more. We think everyone in the world should have access to the best computing has to offer. We provide the platform for original equipment manufacturers (OEMs) and developers to build compelling computing devices (smartphones, tablets, TVs, wearables, etc) that run the best apps/services for everyone in the world.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $138000 - $197000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Provide expert data science guidance, enabling data-driven decisions that accelerate development and improve efficiency.
• Influence the team roadmap, advocating the development of the right tools and processes that empower engineers to build better products faster.
• Work with the Backup and Restore and Setup Specialist teams to build a high-quality Android Onboarding journey with a seamless, effortless, and polished experience.
• Work closely with the Clarity team (AOB metrics team) to safeguard the health of the Android Onboarding experience and empower developers to implement feature-specific telemetry on a robust, scalable, and user-friendly infrastructure, facilitating early detection and mitigation of regressions.
• Partner with the Settings team to understand the usage of various surfaces to ensure the Settings API/appFunction provides a consistent mechanism for authorized applications (Gemini and OEM AI agents) to access and modify all device settings.

Minimum qualifications:

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  
• 5 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL), or 2 years work experience with a Master's degree.

Preferred qualifications:

• Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.