AI Search Engineering Analyst, Safety Risk and Platform

Google•Mountain View, CA

3d•$132,000 - $189,000

About The Position

In this role, you will help protect Google Search users from spam and harmful content. You will use investigative and technical skills to identify and prevent manipulative behavior, contribute to developing and enforcing spam guidelines, and partner with engineering teams to improve search ranking algorithms. The role involves addressing complex abuse and quality issues through data analysis, producing intelligence about emerging threats, and improving tools and automated systems. Google Search aims to provide a universally accessible and useful experience for people around the world.

Requirements

Bachelor's degree in a quantitative field such as Statistics, Econometrics, Computer Science, Mathematics, or Engineering, or equivalent practical experience.
At least 2 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.
At least 2 years of experience managing projects and defining project scope, goals, and deliverables.

Nice To Haves

Master's degree in a quantitative field such as Statistics, Computer Science, Mathematics, or Engineering.
At least 3 years of experience in threat intelligence, data science, trust and safety, fraud analysis, or a similar role.
At least 2 years of experience or familiarity with one or more of SQL, R, Python, or C++.
At least 2 years of experience or familiarity with machine learning systems.
Experience with SEO, website development, or as a website owner or manager.
Experience with HTML, JavaScript, Python, or C++.

Responsibilities

Investigate and analyze complex patterns of abuse on Google Search, using data-driven insights to develop countermeasures and enhance platform security.
Analyze large datasets to identify trends, patterns, and anomalies that may indicate abuse or quality issues within Google Search.
Translate complex technical analyses into insights for technical and non-technical stakeholders.
Produce intelligence reports on emerging attack vectors, system vulnerabilities, and adversary tactics targeting Large Language Model (LLM) architectures.
Improve tools and automated systems through data analysis and technical expertise, and present findings to stakeholders.
Analyze and solve complex problems using data and statistical methods.
Contribute to the development and enforcement of spam guidelines.
Partner with engineering teams to enhance search ranking algorithms.