Staff Data Scientist, Consumer Shopping

Key Skills

Data science techniques, Python Programming, R Programming, SQL

Job Description

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.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

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.