Product Data Scientist, Shopping Analytics

Google; United States; On-site; USD 138,000 - 197,000; Full time

Benefits offered by this job

Health coverage

401(k) match

Paid time off 20 days/year

Sick time 40 hours/year

Maternity leave

Holidays

Job summary

Google is seeking a Product Data Scientist for its Consumer Shopping team to analyze data, build scalable insights, and partner with Engineers and Product Managers to improve shopping experiences across surfaces like Search, AI Mode, and Gemini.

The role emphasizes end-to-end analytics, experimentation, and delivering actionable recommendations to influence product decisions for Google's global user base. Location choices include Mountain View, Kirkland, and other U.S. cities.

Qualifications

• Bachelor’s degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or related quantitative field, or equivalent practical experience.
• 5 years of work experience with analysis applications and coding (Python, R, SQL) or 2 years with a Master’s degree.

Responsibilities

• Work with large, complex data sets and solve difficult, non-routine analysis problems.
• Build and prototype analysis pipelines iteratively to provide insights at scale.
• Interact cross-functionally with leaders and teams, working with Engineers and Product Managers to identify opportunities for design and to assess improvements for Google products.
• Make business recommendations with effective presentation of findings at multiple levels of stakeholders.
• Research and develop analysis and methods to improve the quality of Google's user facing products.

Education

Bachelor's degree in quantitative field

Master's degree in quantitative field

Tools

Python

R

SQL

Job description

Google is seeking a Product Data Scientist for its Consumer Shopping team to analyze data, build scalable insights, and partner with Engineers and Product Managers to improve shopping experiences across surfaces like Search, AI Mode, and Gemini.

The role emphasizes end-to-end analytics, experimentation, and delivering actionable recommendations to influence product decisions for Google's global user base. Location choices include Mountain View, Kirkland, and other U.S. cities.