Senior Product Data Scientist, Google Shopping

Google • Mountain View, CA

2d • $163,000 - $237,000

About The Position

In this role, you will be a passionate, engineering-minded Data Scientist who is eager to innovate data science using GenAI tools and build data products. You will be a full-stack expert who can bridge the gap between software engineering, data engineering, and data science.
The US base salary range for this full-time position is $163,000-$237,000 + 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 [https://careers.google.com/benefits/].

Requirements

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

Nice To Haves

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

Responsibilities

• Provide data-driven perspectives on product direction and opportunities. Define, track, and analyze key metrics and attribution mechanisms to guide product development.
• Conduct analyses to identify the significant opportunities for improving the Shopping Graph. Identify and advocate novel and innovative data science approaches.
• Communicate complex findings and recommendations. Operate with a high degree of autonomy, managing projects from conception to impact. Contribute towards building a data science team that has engineering style work quality.
• Build innovative data products, including self-serve tools, experimentation frameworks, automated rating systems, and human evaluation platforms.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level