Data Scientist, Product, Google Ads Billing
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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
- Perform technical analyses with unstructured data (e.g., logs) to assess success of Billing initiatives in driving better user billing workflows.
- Design and evaluate experiments to help the team understand how product changes affect advertiser experience. Identify methodologies for the team to identify directional impact.
- Investigate fundamental business and product strategy questions. Deliver deep insights on specific topics and areas to provoke new feature/product ideas, or new interventions to drive improved advertiser policy and billing experiences.
- Drive strategic analysis and reporting for business health metrics, focusing on retention, cost savings and performance.
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