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Open nowFirst seen 4 hours ago

Staff Product Data Scientist

Google3,357 open roles

Where
Sunnyvale, CA, USA; Boulder, CO, USA; New York, NY, USA; Seattle, WA, USA
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Your applicationOpen nowStaff Product Data ScientistGoogle · Sunnyvale, CA, USA; Boulder, CO, USA; New York, NY, USA; Seattle, WA, USA

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Google's own form.

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The clock on this job

Early applications get read.

8.2% of postings close within 7 days. Measured by our own scanner across the market. Google postings stay open a median of 26 days.

Share of postings closed within
  1. 1.9%1 day
  2. 3.8%3 days
  3. 8.2%7 days
  4. 15.2%14 days
  5. 34.1%30 days
This job: first seen 4 hours ago

Google median: 26 days open

The posting

The application window will be open until at least October 23, 2026. This opportunity will remain online based on business needs which may be before or after the specified date.

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; Boulder, CO, 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.
  • 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 with a Master's degree).
  • 8 years of experience with core product analytics concepts, including user engagement metrics, funnel analysis, and A/B testing infrastructure.
  • 8 years of experience in data modeling, designing semantic layers and metric stores that power organizational consumption.
  • Experience operating distributed data processing engines.

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

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.

The Collab Data Science team shapes decision-making and provides actionable insights to guide product development for Drive, Docs, Sheets, Slides, Pics and Vids.

As a Data Scientist/Analytics Engineer, you will work closely with product and engineering teams to build products part of Workspace enjoyed by 3B+ users every month.

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

US: $192000 - $278000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Lead the research and development of metric frameworks and methodologies to evaluate the effectiveness, user adoption, and efficiency of Generative AI and agentic tooling within Workspace products.
  • Partner with product engineering and central data infrastructure teams across the organization to clarify ambiguity, define roles, and manage multi-team telemetry and infrastructure projects from inception to execution.
  • Design and build scalable data models and analytical architecture that connect data across distinct product domains, ensuring cohesion.
  • Scope and manage initiatives to enable self-serve analytics by designing unified semantic layers, metric stores, executive dashboards, and AI-powered self-serve tooling.
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