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.

As an Engineering Analyst, you will work to discover, measure and mitigate user trust risks in Search through automated and scalable solutions. This would include working on Search results and various Search features with a focus on deceptive behaviors (e.g., webspam, scams, etc.). You will build relationships and work closely with Search Engineers, Product Managers, and UX specialists to protect Google Search users from spam and harmful content. You will apply your problem-solving and technical skills to identify and prevent manipulative and deceptive behaviors, contribute to the development and enforcement of spam guidelines, and partner with engineering teams to enhance search ranking algorithms. Our aim is to resolve problems at scale by working with engineers on automated product protections, Large Language Model solutions, and/or through vendor support.

This role will be exposed to graphic, controversial, and/or upsetting content.

At Google we work hard to earn our users’ trust every day. Trust & Safety is Google’s team of abuse fighting and user trust experts working daily to make the internet a safer place. We partner with teams across Google to deliver bold solutions in abuse areas such as malware, spam and account hijacking. A team of Analysts, Policy Specialists, Engineers, and Program Managers, we work to reduce risk and fight abuse across all of Google’s products, protecting our users, advertisers, and publishers across the globe in over 40 languages.

The US base salary range for this full-time position is $147,000-$216,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Develop domain knowledge in Search infrastructure, ranking signals, and products. Develop prompt-based AI Raters that can evaluate content safety in Google products.

• Investigate and analyze complex patterns of badness and abuse on Google Search, utilizing data-driven insights to develop countermeasures and enhance platform security. Translate complex technical analyses into clear, concise, and actionable insights for both technical and non-technical stakeholders.

• Analyze large datasets to identify trends, patterns, and anomalies that may indicate abuse or quality issues within Google Search.

• Collaborate effectively with cross-functional teams, including Engineering, Product, Policy, and Legal, to develop and implement robust solutions that enhance search quality and user trust.

Minimum qualifications

• Bachelor's degree or equivalent practical experience.

• 5 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.

• 5 years of experience managing projects and defining project scope, goals, and deliverables.

• Experience with SQL, R, Python, or other programming/scripting languages to manipulate datasets.

Preferred qualifications

• Master's degree in a quantitative discipline.

• 5 years of experience with one or more of the following languages: SQL, R, Python, or C++.

• 5 years of experience with machine learning systems.

• Excellent problem-solving and critical thinking skills, with attention to detail in an ever-changing environment.