About The Position

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 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 be at the heart of Google's commitment to building innovative and safe products, safeguarding the integrity of its platforms by delivering actionable and objective content abuse insights as a member of the Trust and Safety Responsible AI Testing team. As a part of the Responsible AI Testing Sustainability team, you will drive a transformation in how AI testing is approached, partnering across Trust and Safety, product, and engineering teams to integrate AI and automation, turning AI insights into action. This role works with sensitive content or situations and may be exposed to graphic, controversial, and/or upsetting topics or 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.

Requirements

  • Bachelor's degree or equivalent practical experience.
  • 7 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.
  • 7 years of experience managing projects and defining project scope, goals, and deliverables.

Nice To Haves

  • Master's degree in a quantitative discipline.
  • 7 years of experience with machine learning systems.
  • 7 years of experience with one or more of the following languages: SQL, R, Python, or C++.
  • Experience with modeling, experimentation, and causal inference.
  • Excellent problem-solving and critical thinking skills with attention to detail in an ever-changing environment.

Responsibilities

  • Build scalable scripts and workflows using SQL and Python to automate data collection, enrichment, and delivery, maximizing the team's impact.
  • Serve as a bridge between technical and non-technical teams, effectively translating trust and safety intelligence needs into clear, actionable requirements for data solutions.
  • Establish standardized processes and methodologies for data analysis that can be applied across various topics, ensuring consistency and efficiency in generating valuable insights.
  • Work autonomously to identify and solve problems and collaborate effectively within a team to develop comprehensive solutions.
  • Transform raw data into compelling visualizations and reports that clearly communicate key findings and actionable recommendations to stakeholders across the organization.
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