info_outline
X 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:
Seattle, WA, USA; New York, NY, USA; Sunnyvale, CA, 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 of experience with 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 jobThe Workspace Collab Data Science team empowers product teams for Drive, Docs, Sheets, Slides, Vids (and more) through development of key metrics, data-driven insights, modeling, experimentation and other forms of causal inference to grow product adoption and AI usage.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $192000 - $279000 (USD) 20% bonus target bonus equity benefits
Learn more about benefits at Google .
Responsibilities- Define, own and evolve product success metrics. Report, analyze and forecast trends of key product metrics and make recommendations to improve them.
- Lead the design, analysis, and interpretation of product experiments. Proactively perform data exploration to understand user behavior and identify opportunities for improving and growing Workspace products.
- Apply technical expertise with observational data analysis, modeling, and causal inference to answer the most important product questions.
- Partner with Product, Engineering, UX and cross-functional teams to influence, prioritize and support product strategy.
- Deliver effective presentations of data-driven insights and recommendations to multiple levels of stakeholders.
