Senior Business Data Scientist, Trust and Safety Business Analytics

About the role

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.

• Experience creating dashboards, data visualizations, or business reports.

PREFERRED QUALIFICATIONS:

• 6 years of experience using analytics to solve product or business problems,

coding (e.g., Python, R, SQL), querying databases or statistical analysis.

• 6 years of experience driving business outcomes using data analysis,

statistical analysis, data pipelines, and dashboard solutions.

• Experience in Trust and Safety, content moderation, or risk analysis.
• Experience leading complex technical projects, influencing cross-functional

teams.

• Experience with agentic statistical modeling, root cause analysis, and large

language model (LLM) multi-agent system engineering.

• Excellent communication and stakeholder management skills to translate

complex data into clear, actionable insights.

ABOUT THE JOB:

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.

Individual pay is determined by factors including job-related skills,

experience, and relevant education or training.

US: $163000 - $236000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google

[https://www.google.com/about/careers/applications/benefits/].

RESPONSIBILITIES:

• Develop an understanding of products, Trust and Safety (T&S) manual and

automated processes, tools, and customer expectations to design scalable

measurements that support reporting needs.

• Build and scale AI-based systems in partnership with Engineering teams,

accurately measure the efficiency gains.

• 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.

• Collaborate with stakeholders to understand the domain, business goals, and

data infrastructure context.