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Job Type
Full Time
Job Details
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 (e.g., extracting insights, performing statistical analysis, or solving business problems), and coding (e.g., Python, R, SQL).
- Experience in experimental design (e.g., A/B, multivariate, Bayesian methods) and incremental analysis.
- Experience working with large and multiple datasets/data warehouses and ability to pull from such data sets using relevant tools and coding.
- Build models and frameworks to understand the opportunity size of Customer Engineering (CE) initiatives. Enable informed decisions, contribute to annual and quarterly objectives and key results setting.
- Build an understanding of the large, complex data sets used by CE and our partner teams. Work with engineering teams to plug gaps in logging and data infrastructure.
- Build data aggregation and analysis pipelines, designing new metrics, and creating dashboards and visualizations around them.
- Determine metric definition for each workstream to ensure alignment/rollup to team and organization objectives and key results.
- Improve experimentation velocity and analysis turnaround time through adoption of self-service tools such as RASTA.
About the Company
Google Inc.
Mountain View, CA, United States
Build for everyone Since our founding in 1998, Google has grown by leaps and bounds. Starting from two computer science students in a university... Read more