Engineering Analyst, Trust and Safety, Strategic Intelligence
Mid • On-site
$147,000 - $216,000/yr
Washington D.C., DC
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.
5 years of experience with SQL and Python (or similar languages) for data transformation and analysis
3 years of experience with foundational concepts in machine learning, including model evaluation and prompt engineering.
Preferred qualifications:
Experience with metrics development and A/B testing (modeling, experimentation, and causal inference).
Experience in data transformation, structured labeling, and creating machine-readable datasets.
Experience in technical Trust and Safety, threat intelligence, risk analysis, or related roles, including abuse detection, adversarial tactics and model evaluations for safety and robustness.
Ability to navigate imperfect data and prioritize under uncertainty in a changing threat landscape.
Familiarity with risk intelligence workflows (collection, analysis, dissemination).
Excellent communication skills to collaborate with analysts, engineers, and policy stakeholders.
About the job
The Trust and Safety Intel Analysis team's mission is to deliver risk intelligence to drive decision making and systematic mitigation. We proactively identify, analyze, and prioritize trust risks, empowering Google teams and executives with actionable intelligence to make informed decisions and take timely action to mitigate threats, enhance user safety, and maintain trust in Google products.
As an Engineering Analyst on the Trust and Safety Intelligence team, you will bridge between our intelligence analysts and our technical and product teams. You will be responsible for transforming qualitative intelligence on emerging threats and abuse patterns into operational, machine-readable data, evaluations, and prompt sets that directly support product, enforcement, and policy teams.
You have a passion for operationalizing intelligence and an understanding of how to structure, unstructured data for machine consumption. You will work with qualitative analysis as you are with structured data sets and technical systems. Your work will enable the company to anticipate and respond to adversarial misuse, strengthen detection and enforcement systems, and scale policy into practice.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
Own expertise in SQL and familiarity with Python to design, build, and maintain automated data pipelines, reporting dashboards, and reusable frameworks which includes the skill to gather requirements from non-technical stakeholders and transform data into clear, actionable visualizations and reports.
Act as a link between intelligence analysts and product, engineering, and policy teams which includes communicating with intel analysts and collaborating to ensure their outputs are integrated into product features and enforcement systems, and creating feedback loops that inform policy and system improvements.
Develop and maintain evaluation datasets and metrics to measure the efficacy and coverage of intelligence-to-enforcement pipelines. This involves assessing the performance of automated systems in detecting and mitigating risks.
Translate qualitative threat intelligence into technical artifacts, including structured data and machine-readable prompt sets for Large Language Models (LLMs).
Google
Google LLC started as a PhD project by Larry Page and Sergey Brin in 1998 at Stanford University. Google LLC has blossomed into a behemoth of the tech world. With its mission to organize the world's information and make it universally accessible and useful, Google’s search engine is its crown jewel. Online advertising, via AdWords and AdSense, forms the backbone of its financial success. Beyond search, Google has ventured into cloud computing, hardware, and software development. The innovative PageRank algorithm revolutionized search engine technology, and surviving the dot-com bubble burst and going public in 2004 spurred its meteoric growth. Acquiring YouTube stands as a testament to Google’s strategic expansion.