Business Data Scientist

• Acquire deep understanding of product, Trust and Safety 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 uncaught badness rate, creating standardized, robust, and defensible measurements applicable across products and violation areas.
• Design, implement and own technical implementation of production-level data pipelines, documentation, check-in process, etc.
• Build and scale AI-based content rating systems in partnership with Engineering teams, accurately measure the efficiency gains from the same.
• Collaborate with and influence business and engineering stakeholders to ensure our data is telling the right story and is helping stakeholders make data backed decisions. Present findings and business recommendations to multiple levels of stakeholders and leadership teams.

Minimum qualifications:

• Master's degree in a quantitative discipline such as Statistics, Engineering, 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 large global business managing business outcomes using data analysis, statistical analysis, data pipelines (e.g. SQL), and dashboard solutions (e.g., Tableau, Qlik).
• 3 years of experience utilizing data science techniques to solve complex business challenges, including using statistical modeling techniques and programming languages (e.g., Python, R) for data analysis.
• Experience in leading complex technical projects, influencing cross-functional teams and navigating ambiguous environments.
• Experience in Trust and Safety, content moderation, or risk analysis.
• Excellent communication, people management, and stakeholder management skills, with the ability to translate data into clear, actionable insights for non-technical audiences.

At Google we work hard to earn our users’ trust every day. Gaining and retaining this trust is critically important to Google’s success. The Trust and Safety team reduces risk and protects the experience of our users and business partners in more than 40 languages and across Google's expanding base of products. We defend Google's integrity by fighting spam, fraud and abuse, and develop and communicate product policies. We work with a variety of teams from Engineering to Legal, Public Policy and Sales Engineering to set policies and combat fraud and abuse in a scalable way, often with an eye to finding industry-wide solutions. Trust and Safety team members are motivated to find innovative solutions, and use technical know-how, user insights and proactive communication to pursue the highest possible quality and safety standards for users across Google products.

• Master's degree in a quantitative discipline such as Statistics, Engineering, 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.