Senior Staff Product Data Science Manager, Monetization - Sunnyvale, CA, USA

Only for registered members Sunnyvale, CA, USA, United States

16 hours ago

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info_outlineXIn 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) wit ...
Job description
info_outlineXIn 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 (statutory, where applicable); 5 days/event (discretionary)
  • 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; Kirkland, WA, USA; New York, NY, USA.

Minimum qualifications:

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

Preferred qualifications:

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


About the job

Google Workspace from Google Cloud is a smart, simple, and secure family of productivity apps. They are designed to simplify work and increase the productivity of teams, with real-time collaboration built in from the start. With Google Workspace, information can flow freely between devices, apps, people, and teams, so great ideas never get left in the margins again.

As a Product Data Science leader in Workspace Monetization, you will play a key role in growing the Workspace business and impacting millions of businesses worldwide. You will own the measurement strategy of Workspace monetization products, deepen our understanding of the business, identify growth levers, and influence our growth roadmap. Additionally, you will drive analytics infrastructure investments and improve our data foundation. You will have a record of establishing a data-driven culture by infusing critical measurement and analysis into team operations. You should possess excellent people-management and communication skills, with the ability to influence cross-functional teams and align incentives across products.

The US base salary range for this full-time position is $227,000-$320,000 + 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

  • Lead measurement strategy and define analytics infrastructure needs to ensure the accuracy and quality of key decisions for Workspace monetization initiatives.
  • Influence monetization strategy (product feature roadmaps, pricing, bundling strategy, etc.) with analytical efforts, ensuring Workspace and Cloud AI OKRs are informed by analytical insights.
  • Partner closely with Engineering, Product, UX, Sales, and Finance to influence and execute monetization strategies.
  • Lead the design, analysis, and interpretation of product experiments. Apply technical expertise in observational data analysis, modeling, or causal inference to answer critical product questions.
  • Mentor and develop data science talent.


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