About the job

Trust & Safety team members are tasked with identifying and taking on the biggest problems that challenge the safety and integrity of our products. They use technical know-how, excellent problem-solving skills, user insights, and proactive communication to protect users and our partners from abuse across Google products like Search, Maps, Gmail, and Google Ads. On this team, you're a big-picture thinker and strategic team-player with a passion for doing what’s right. You work globally and cross-functionally with Google engineers and product managers to identify and fight abuse and fraud cases at Google speed - with urgency. And you take pride in knowing that every day you are working hard to promote trust in Google and ensuring the highest levels of user safety.

In this role, you will have the opportunity to shape the future of people discovering information through Google Search with user and business impact.

Responsibilities

• Use technical judgment to drive project delivery, test proposals and identify risks. Manage multiple projects, manage cross-functional teams.

• Collaborate with other teams and functions (e.g., Engineering, Product Managers, Legal, Policy).

• Perform data analysis to provide insights that help to identify and fight abuse across the products.

• Lead and manage cross-functional, multi- quarter technical trust projects (e.g., application of Generative AI (GenAI) frameworks like agentic Artificial Intelligence (AI), Large Language Model (LLM)). Analyze and debug escalations and identify trends that can indicate product risks.

Minimum qualifications

• Bachelor's degree or equivalent practical experience.

• 4 years of experience in data analytics, Trust and Safety, policy, cybersecurity, or a related field.

• 4 years of experience in data analysis, working with databases, and querying (e.g., SQL, MySQL).

Preferred qualifications

• Master's degree in a related field.

• Experience in SQL, building dashboards, data collection/transformation, visualization/dashboards, or with programming language (e.g., Python).

• Experience in working with abuse, spam, fraud or malware.

• Experience with machine learning.

• Experience in generating summary statistics, and developing insights from quantitative and qualitative data.

• Excellent communication and presentation skills, with the ability to collaborate cross-functionally.