Senior Data Scientist, Product, Google Shopping

Key Skills

Aartificial intelligence, Data science techniques, Python Programming, R Programming, SQL

Job Description

Minimum qualifications:

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
• 8 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 5 years of experience with a Master's degree).

Preferred qualifications:

• Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
• Experience building commerce/shopping related products.

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

• Act as a consultant and thought partner to Engineering and Program Management leads, providing data-driven perspectives on product direction and opportunities. Define, track, and analyze key metrics and attribution mechanisms to guide product development.
• Conduct deep-dive analyses to identify the most significant opportunities for improving the Shopping Graph. Identify and advocate new investigative approaches.
• Design and implement analysis (evals, log analysis etc.) to measure the impact of Shopping Graph data on key shopping experiences (especially AI-powered experiences like AIM and Gemini).
• Communicate complex findings and recommendations clearly and effectively to technical and non-technical stakeholders, including executive leadership.
• Operate with a high degree of autonomy, managing projects end-to-end from conception to impact.