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# Engineering Analyst, Trust and Safety, Egregious Harms

- **Company:** Google LLC
- **Location:** Washington, DC, United States
- **Experience:** Experienced
- **Salary:** $132,000.0 - $189,000.0
- **Contract:** Permanent contract
- **Skills:** Google AdWords, Data Analysis, Google Tools, Python (Programming Language), Azure Machine Learning, SQL Databases, Scripting, Large Language Models, Machine Learning Operations
- **Published:** August 20, 2026
- **Apply:** https://dejobs.org/x/x/5D42DE0C873B4D5FA51033B899260C6B/job/

## About the Role

Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area., * 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.
 * Experience with one or more of the following languages: SQL or Python., * Master's degree in a quantitative discipline.
 * Experience with scripting language, machine learning tools, techniques and systems (including large language models).
 * Knowledge of current abuse techniques and practices.
 * Ability to work with a variety of stakeholders to gather requirements, explain models, and iterate to make improvements.
 * Excellent problem-solving and critical thinking skills with attention to detail in an ever-changing environment.
 * Excellent communication with an ability to describe technical implementations or analyses to a non-tech audience.

About the job

Trust and 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.

## Description

As an Engineering Analyst within the Trust and Safety team, you will be part of a global team that ensures the seamless detection and enforcement of some of the most egregious online harms (e.g., child sexual abuse materials, non-consensual intimate imagery, violent extremism). Through close partnerships with Product, Engineering, Policy, and Legal, you will leverage your technical acumen to design and develop novel solutions to further Google's ability to fight this abuse worldwide.At Google we work hard to earn our users' trust every day. Trust and 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.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $132000 - $189000 (USD) + 15% bonus target + equity + benefits, * Perform data analyses to derive insights that help identify emerging threats and fight abuse across our products.

 * Identify opportunities for the improvement of Google's detection and enforcement systems as well as for automation.
 * Lead multiple interdependent projects of moderate to high complexity and scope, coordinating cross-functionally to ensure alignment on objectives and key results.
 * Analyze statistics (e.g., precision, recall) about the performance of technical models (ML systems, classifiers, Large Language Model (LLMs) and recognize nuanced, easily missed problems in the performance of these systems.
 * Review or be exposed to sensitive or graphic content as part of core role.


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