Senior Staff Research Data Scientist, Workspace GenAI
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- 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
Minimum qualifications:
- Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
- 10 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of work experience with a PhD degree.
Preferred qualifications:
- 12 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 10 years of work experience with a PhD degree.
About the job
Empower the Google Workspace ecosystem with intelligent capabilities including Gmail, Docs, and Meet by delivering actionable insights and defining the critical metrics that drive quality and high-impact organizational opportunities.
The US base salary range for this full-time position is $262,000-$369,000 + 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.Responsibilities
- Provide high-level technical direction for the Workspace Data Science (WDS) GenAI Foundations team, fostering a culture of rapid experimentation and leading the organization through complex technical transitions.
- Utilize AI models and tools as integral components for evaluating, synthesizing, and understanding complex datasets.
- Develop new methodologies to improve the performance of Google's models through better training data, including data acquisition, and insights.
- Drive Data Science-led horizontal experimentation and evaluation across key components of the Workspace GenAI Platform.
- Act as a technical partner, collaborating closely with Research, Engineering, and Product teams (Workspace and Google DeepMind).
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