Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.
In this role, you will be responsible for designing and developing metrics and measurements needed to support Trust and Safety (T&S) across various Google products, including Search, Ads, Shopping, Publishers, and YouTube. You will ensure stakeholders have the product, support, and operations data they need to make crucial business decisions. You will have the opportunity to design innovative data solutions and solve problems using Google’s production data infrastructure to drive business optimization and meet regulatory reporting requirements.
The US base salary range for this full-time position is $163,000-$237,000 + 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
- Acquire an understanding of the product, trust and safety (T&S) manual and automated processes, tools, and customer expectations. Design and develop scalable measurements to support reporting needs.
- Lead the statistical design, definition, and implementation of metrics such as the uncaught badness rate, creating standardized, and defensible measurements applicable across products and violation areas.
- Design, implement, and own the technical implementation of production-level data pipelines, documentation, and the code check-in process.
- Build and scale artificial intelligence (AI)-based content rating systems in partnership with engineering teams and measure the efficiency gains accurately from the same.
- Collaborate with business and engineering stakeholders to ensure our data is telling the right story and helping stakeholders make data-backed decisions. Present findings and business recommendations to multiple levels of stakeholders and leadership teams.
Qualifications
Minimum qualifications:
- Master's degree in a quantitative discipline (e.g., Statistics, Engineering, and Sciences), or equivalent practical experience.
- 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
Preferred qualifications:
- 6 years of experience in a global business driving business outcomes using data analysis, statistical analysis, data pipelines (e.g., SQL), and dashboard solutions (e.g., Tableau, Qlik).
- 3 years of experience in utilizing data science techniques to solve business issues, including using statistical modeling techniques and programming languages (e.g., Python or R) for data analysis.
- Experience in trust and safety, content moderation, or risk analysis.
- Experience in leading technical projects, influencing cross-functional teams and navigating ambiguous environments.
- Excellent communication, people-management, and stakeholder skills, with the ability to translate data into clear, actionable insights for non-technical audiences.