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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 (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:
Atlanta, GA, USA; Washington D.C., DC, USA.
Minimum qualifications: - Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
- 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.
Preferred qualifications: - 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.
- 3 years of experience as a people manager within a technical leadership role.
About the jobAt Google we work hard to earn our users' trust every day. Trust & Safety is Google's team of abuse fighting and user trust experts working to make the internet a safer place. A team of Analysts, Policy Specialists, Technical Experts, and Program Managers, we work to reduce risk and fight abuse across all of Google's products, protecting our users, advertisers, and publishers across the globe in over 40 languages.
Within the Trust and Safety organization, Data Science leverages the power of data to deliver actionable insights that inform decision-making, drive operational excellence and foster user trust in Google products. We use data science to empower abuse fighting at scale and partner with Google products and services across our pillars of Operational Excellence, Applied Gen AI Safety, Applied Data Utilities, and Advanced Measurement.
As a Data Science Manager in Trust & Safety, you will work with a global team of data scientists and analysts and drive strategic roadmaps and partnerships across the team pillars and foster growth and happiness of a high performing team. You are an experienced data science leader, who will grow in a cross-product environment, enjoys problem solving and understands how to use the power of data science to quantify and optimize operations. You will collaborate and communicate effectively with a multi-disciplinary team of engineers and abuse analysts on a wide range of problems. You will use your communications skills to represent the team with a global audience, translating the team's technical work and connecting it to business impact.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $300000 (USD) 20% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities - Lead a team of high performing data scientists and analysts across Americas (AMER) and EMEA regions. Foster team growth, culture, innovation and collaboration for a team who consistently partners with other teams to drive impact.
- Define and drive team roadmap and partnerships, identifying areas where data science can significantly multiply Trust & Safety's impact in keeping users safe and prioritizing team's engagements across numerous opportunities.
- Partner effectively with teams of cross-functional disciplines and focus areas.
- Articulate the team's work and deliverables to the cross-functional audience, translating technical concepts to business impact.
- Identify and support the team in solving for both existing and emerging data science opportunities, for example in AI testing standards, responsible AI and risk identification and quantification.
