Engineering Analyst, Trust and Safety Strategic... @ Google
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Minimum Qualifications
Bachelor's degree or equivalent practical experience. At least 5 years of experience in data analysis, project management, and technical skills including SQL and Python. 3 years of experience in machine learning fundamentals.
Preferred Qualifications
Experience with metrics development, A/B testing, data transformation, structured labeling, and creating machine-readable datasets. Familiarity with technical Trust and Safety roles including abuse detection and adversarial tactics plus strong communication skills.
About The Job
The Trust and Safety Intel Analysis team delivers risk intelligence to drive decision making and threat mitigation. In the role of Engineering Analyst, you will bridge intelligence analysis with product, engineering and policy teams by transforming qualitative threat intelligence into operational data and technical artifacts.
Responsibilities
- Design and maintain automated data pipelines and dashboards using SQL and Python.
- Translate qualitative intelligence into machine-readable datasets and prompt sets.
- Act as a conduit between intelligence analysts and technical teams.
- Develop robust evaluation datasets and metrics for intelligence-to-enforcement pipelines.
- Collaborate with stakeholders to integrate intelligence into product and enforcement systems.
Compensation
The US base salary range for this full-time position is $147,000-$216,000, complemented by bonus, equity, and benefits.
Equal Opportunity
Google is proud to be an equal opportunity workplace. We encourage candidates from all backgrounds to apply.
Key skills/competency
- Data Analysis
- SQL
- Python
- Machine Learning
- Risk Intelligence
- Trust and Safety
- Project Management
- Data Transformation
- Threat Analysis
- Communication
How to Get Hired at Google
🎯 Tips for Getting Hired
- Customize your resume: Tailor skills with SQL, Python, analytics.
- Showcase project experience: Highlight data transformation projects.
- Emphasize analytics expertise: Include machine learning and risk analysis.
- Prepare examples: Use real data challenges and successes.