AI Trust & Safety Data Analyst (Search)

Google Inc.; Dublin; On-site; EUR 90,000 - 92,000; Full time

Benefits offered by this job

Equity

Bonus target 15%

Job summary

Google's Dublin-based Share Engineering Analyst role focuses on analyzing data to identify trends and insights that help protect users from abuse and fraud. You will collaborate with Trust & Safety, Policy, and Product teams to implement policy-informed safeguards in a fast-moving environment.

The position emphasizes ML infrastructure, model evaluation, data processing, and close work with engineering teams to deliver measurable improvements.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 2 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.
• 2 years of experience utilizing Python and SQL to solve engineering problems.
• Experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).

Responsibilities

• Establish metrics to benchmark Generative-AI issues and quantify improvements.
• Develop datasets and run evals for engineers to evaluate and improve Search, Labs & Assistant products.
• Perform complex data analyses to derive insights that help identify and fight abuse across our products.
• Analyze and debug escalations and identify risks for product policies.
• Use technical judgement to drive project delivery and improve workflows.

Skills

Data analysis

Python

SQL

ML design & infra

Policy & abuse analytics

GenAI risk awareness

Statistics & hypothesis testing

Education

Bachelor's degree or equivalent practical experience

Job description

Google's Dublin-based Share Engineering Analyst role focuses on analyzing data to identify trends and insights that help protect users from abuse and fraud. You will collaborate with Trust & Safety, Policy, and Product teams to implement policy-informed safeguards in a fast-moving environment.

The position emphasizes ML infrastructure, model evaluation, data processing, and close work with engineering teams to deliver measurable improvements.