Senior Staff Data Scientist, Workspace AI Foundations

Google LLC; Seattle (WA); On-site; USD 240,000 - 333,000; Full time

Benefits offered by this job

Health, dental, vision, life, and long

Disability insurance

401(k) with company match

Paid Time Off: 20 days/year

Sick Time: 40 hours/year (Seattle up

Maternity Leave: 28-30 weeks

Baby Bonding Leave: 18 weeks

13 paid holidays/year

Job summary

Google LLC in Seattle is seeking a Staff/Senior Staff Product Data Scientist for the Workspace GenAI Foundations team. You will shape measurement frameworks and data pipelines across AI pillars to impact productivity for billions of users.

As a technical leader, you will collaborate with senior Product, Engineering, and Research leaders, guiding strategy, model evaluation, and data architecture. Individual pay is determined by skills, experience, and education.

Qualifications

• Bachelor's degree in a quantitative field is required (stats/math/DS/engineering/physics/economics).
• 13 years of analytics experience solving product/business problems with statistical analysis and coding (or 10 years with a Master's).
• Experience with Python, R, and SQL.

Responsibilities

• Lead horizontal metric and evaluation frameworks that quantify engagement, productivity gains, and end-to-end system quality across GenAI models, agentic tooling, context grounding, and safety.
• Deliver executive-ready insights and recommendations that guide product roadmaps, organizational transitions, and resource allocation.
• Work on challenges across behavioral, telemetry, and evaluation datasets to identify user adoption, quality or reliability gaps, latency/cost trade-offs, and new methodologies to improve performance.
• Define upstream logging and telemetry standards, design scalable data models and ETL pipelines, and build unified semantic layers and self-serve analytics that connect data across Workspace domains.
• Drive experimentation, observational causal inference, and rigorous model evaluations—leveraging AI models/tools as well as human and automated rating systems.

Skills

Analytics experience

Statistical analysis

Python

R

SQL

Education

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

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

Tools

ETL pipelines

Data architecture

Job description

In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:

• Health, dental, vision, life, disability insurance
• Retirement Benefits: 401(k) with company match
• Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
• Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
• Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
• Baby Bonding Leave: 18 weeks
• Holidays: 13 paid days per year

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sunnyvale, CA, USA; New York, NY, USA; Seattle, WA, USA.

Minimum qualifications:

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
• 13 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 10 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).

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.

We empower Workspace with AI, guiding products like Gmail, Docs, Sheets, Slides, Drive, Meet, Chat, and beyond to become truly intelligent. We deliver actionable insights, define the critical metrics, and measure quality, pinpointing the highest-impact opportunities for the entire organization.

As a Staff/Senior Staff Product Data Scientist on the Workspace GenAI Foundations team, you will act as a technical leader and strategic advisor at the intersection of product strategy, model evaluation, and data architecture across our horizontal AI pillars—spanning Agentic Ecosystems, AI Platform, Workspace Intelligence, and Abuse & Safety Protections. Partnering closely with senior Product, Engineering, and Research leaders across Workspace and DeepMind, you will pioneer the measurement frameworks, experimentation methodologies, and foundational data pipelines that shape AI-powered productivity and agentic experiences for over 3 billion users.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $240000 - $333000 (USD) + 25% bonus target + equity + benefits

Responsibilities

• Learn more about benefits at Google .
• Lead horizontal metric and evaluation frameworks that quantify engagement, productivity gains, and end-to-end system quality across GenAI models, agentic tooling, context grounding, and safety.
• Deliver clear, executive-ready insights and recommendations that guide product roadmaps, organizational transitions, and resource allocation.
• Work on challenges across behavioral, telemetry, and evaluation datasets to identify user adoption, quality or reliability gaps, latency/cost trade-offs, and new methodologies to improve performance.
• Define upstream logging and telemetry standards, design scalable data models and ETL pipelines, and build unified semantic layers and self-serve analytics that connect data across Workspace domains.
• Drive experimentation, observational causal inference, and rigorous model evaluations—leveraging AI models/tools as well as human and automated rating systems.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .