Staff Data Scientist, Consumer Shopping
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Minimum qualifications:
- Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
- 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.
Preferred qualifications:
- 10 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of work experience with a PhD degree.
About the job
As a Staff Data Scientist in Consumer Shopping organization, you will evaluate and improve Google's Shopping products. You will collaborate with a multidisciplinary team of engineers and PMs on a wide range of problems. In this role, you will bring statistical, econometric methods to the issues of measuring quality, improving consumer products, and understanding the behavior of our end-users, merchants, and partners and develop, organize and launch experiments and projects across Engineering and Product teams.The US base salary range for this full-time position is $197,000-$291,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.Responsibilities
- Partner with cross-functional teams to leverage advanced economic and causal modeling techniques (e.g., difference-in-differences, instrumental variables, synthetic control) to drive business insights and decision-making.
- Conduct end-to-end analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
- Research and develop analysis and methods to improve the quality of Google's user-facing products.
- Interact cross-functionally with a wide variety of leaders and teams (e.g., Engineering, Product Management) to identify opportunities for design and to assess product improvements.
- Conduct in-depth research and analysis to understand customer behavior, pricing dynamics, and the incremental impact of commerce programs and initiatives.
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