Senior Data Scientist Product, Google Play Games
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Minimum qualifications:
- Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, a related quantitative field, or equivalent practical experience.
- 8 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 5 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.
- 8 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
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
- Design and implement automated and standardized analysis tools (e.g., dashboards), empowering business stakeholders to uncover business opportunities and make informed decisions.
- Scrutinize and validate data integrity throughout the collection process, performing data profiling to identify and comprehend data anomalies, and investigate the root causes of business problems, providing solutions.
- Produce insights and metrics for various technical and business stakeholders.
- Deliver presentations of findings and recommendations to multiple levels of leadership, creating visual displays of quantitative information.
- Follow engineering best practices to create scalable data pipelines and models, engage and influence senior stakeholders and cross-functional partners, obtain buy in for potential solutions, and adapt messaging and suggested recommendations.
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