Data Scientist, Product, Google Play Games
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Minimum qualifications:
- Master's degree in Statistics, Economics, Engineering, Mathematics, a related quantitative field, or equivalent practical experience.
- 3 years of experience working with statistical packages (e.g., R, SAS, Stata, MATLAB, etc.).
- Experience in articulating product questions, pulling data from datasets (e.g., SQL), and using statistics.
Preferred qualifications:
- 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).
- Experience working with multiple datasets/data warehouses, with the ability to pull from data sets using tools and coding.
- Experience in experimental design (e.g., A/B, multivariate) and incremental analysis.
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.
Responsibilities
- Design and implement automated and standardized analysis tools (e.g., dashboards), empowering business stakeholders to uncover business opportunities and make informed decisions.
- Validate and scrutinize data integrity throughout the collection process, performing data profiling to identify and data anomalies.
- Investigate the root causes of business issues, providing solutions that go beyond superficial observations.
- Deliver presentations of findings and recommendations to multiple levels of leadership, creating visual displays of quantitative information.
- Engage and influence executive stakeholders and cross-functional partners, obtain buy-in for potential solutions, adapt messaging and suggested recommendations.
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