Product Data Scientist

Product Data Scientist, Google Play

Minimum qualifications:

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field, or equivalent practical experience.
• 5 years of experience with analysis applications (e.g., extracting insights, performing statistical analysis, or solving business problems), and coding (e.g., 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.

About the job

Help serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next.Google Play offers music, movies, books, apps and games for devices, powered by the cloud. It syncs across devices and on the web. As part of the Android and Mobile team, Googlers working on Google Play do everything from engineering our backend systems, to shaping product strategy, to forming great content partnerships. They make it possible for people to do things like buy an ebook or song on their Android phone, then have it instantly available on their laptop. The Google Play team enhances the Android ecosystem by giving developers and partners a premium store where they can reach millions of users.

Responsibilities

• Own the full data science lifecycle, from problem definition and data extraction to statistical modeling and executive presentation with resolving product tests.
• Design, execute, and interpret A/B tests and multivariate experiments to validate product hypothesis and measure user impact.
• Define and track the Key Performance Indicators (KPIs) that measure product health, such as user engagement and ecosystem health.
• Partner with Product Managers (PMs), Product Marketing Managers (PMMs), Engineers, and User Experience (UX) Researchers to translate raw data into insights and recommendations.
• Apply advanced statistical techniques (e.g., regression, time-series forecasting, and causal modeling) to identify growth opportunities and predict the impact of future features.

Experience Level

Mid Level