GoogleEmployer profile
Data Scientist, Product, Analytics and Operations
Location not specified · 3–83.3 yrs
Experience
- 3–83.3 yrs
Salary
- Not disclosed
Location
- Location not specified
Work mode
- Not specified
Job type
- Full-time
Apply by
- Closing date not listed
Posted
- 13 Oct 35
About this role
Minimum qualifications:- Master's degree in Statistics, Economics, Engineering, Mathematics, a related quantitative field, or equivalent practical experience.
- 3 years of experience with statistical data analysis, data mining, and querying (e.g., SQL).
- 1 year of experience managing analytical projects.
- 5 years of experience with analysis applications (i.e., extracting insights, performing statistical analysis, or solving business problems), and coding (e.g., Python, R, SQL).
- Excellent communication and presentation skills, with the ability to deliver findings of analysis.
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.
Responsibilities
- Drive analysis for Play, focusing on product features and developer experience across Play Apps and Games.
- Partner with Product Manager, Engineering team, Go-To-Market and other Play teams to provide data feed, experiment design and product insights that will improve performance, and ensure proper logging and metrics are available for performance measurement.
- Act as a thought partner to produce insights and metrics for various technical and business stakeholders across Play.
- Deliver effective presentations of findings and recommendations to multiple levels of leadership, creating visual displays of quantitative information.
- Develop framework and build views to measure product success and provide insights at scale.