Staff Product Data Scientist, Google Play App

About the job

Google Play provides apps, games, and digital content services that bring Android devices to life. It’s a Google approach to entertainment, syncing magically across your devices and the web. As part of the Platform and Devices team, working on Google Play, you will do everything from shaping the product strategy, to engineering our backend systems, to forming great content partnerships. You will make it possible for people to do things like buy a game or app on their Android phone, then have it instantly available across all the form factors.

The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.

The US base salary range for this full-time position is $192,000-$278,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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

• Partner with Engineering, Product Management, and other Play/Apps stakeholders to inform strategy, influence with insights, and provide methodological insights and metrics that reduce risk and improve user experience.
• Design and analyze A/B experiments, develop and operationalize novel measurement methodologies, including ensuring proper logging and metrics, to quantify user behavior, engagement, and long-term user value for app features.
• Conduct post-launch and longitudinal analyses to identify growth opportunities, understand long-term impact, and inform future product development.
• Research, develop, and monitor ML models to improve user engagement, including establishing evaluation criteria.
• Develop frameworks to measure product success and deliver effective, visually compelling presentations of findings and actionable recommendations to multiple levels of leadership.