About the job

Google Workspace is a smart, simple, and secure suite of productivity apps—including Gmail, Docs, Drive, Calendar, Sheets, Meet, and Chat. Designed to simplify workflows and boost team productivity, Workspace features real-time collaboration at its core, allowing information to flow freely across devices and teams so that great ideas are never lost.

As a Staff Data Scientist on the Workspace Monetization Product team, you will play a key role in growing the business and impacting millions of users worldwide. In this role, you will partner with product and engineering teams to shape business generation and growth strategies.

The US base salary range for this full-time position is $192,000-$278,000 + 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

• Act as a thought partner to Engineering and Product Management leads, providing data-driven perspectives on product direction and opportunities. Oversee the contributions of others and develop colleagues’ capabilities within your area of specialization.

• Conduct deep-dive analyses to identify the most significant opportunities for growing Workspace business and user value.

• Communicate complex findings and recommendations clearly and effectively to technical and non-technical stakeholders, including executive leadership.

• Own project outcomes by covering problem definition, metrics development, data extraction and manipulation, visualization, and the implementation of statistical models.

• Lead and manage problems that may be ambiguous or lack clear precedent by framing hypotheses and making recommendations that combine problem-solving and product-specific expertise.

Minimum qualifications

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.

• 10 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 8 years work experience and a Master's degree).

Preferred qualifications

• Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.

• 12 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).