AI Safety Protections Data Scientist, Trust and Safety

3 Months ago • 2-5 Years • Data Analyst

Job Summary

Job Description

This AI Safety Protections Data Scientist role within Google's Trust & Safety team focuses on developing scalable safety solutions for AI products. Responsibilities include leveraging machine learning and AI techniques to analyze Google's protection measures, identify shortcomings, and develop actionable insights. The role involves crafting data stories for stakeholders, building automated data pipelines and dashboards, and working with sensitive content. The ideal candidate possesses strong data analysis, project management, and problem-solving skills, with expertise in machine learning and programming languages like Python, R, SQL, and C/C++. Experience in abuse and fraud disciplines is preferred.
Must have:
  • Bachelor's degree or equivalent experience
  • 2+ years data analysis experience
  • 2+ years project management experience
  • Proficient in Machine Learning
  • Programming skills (Python, SQL etc.)
  • Develop scalable safety solutions
Good to have:
  • Master's/Ph.D in quantitative discipline
  • 5+ years relevant work experience
  • Experience in abuse/fraud disciplines
  • Experience with database and scripting languages

Job Details

Minimum qualifications:

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

Preferred qualifications:

  • Master’s or Ph.D degree in a quantitative discipline (e.g., Computer Science, Statistics, Mathematics, Operations Research etc.).
  • 5 years of relevant work experience in a large-scale data analysis or data science setting.
  • Experience in abuse and fraud disciplines, especially focused on web security, harmful content moderation and threat analysis.
  • Experience in programming languages (e.g., Python, R, Julia), database languages (e.g., SQL) and with scripting languages (e.g., C/C++, Python, Java).
  • Proficient in applying Machine Learning techniques to large datasets.
  • Excellent problem-solving and critical thinking skills with attention to detail in an ever-changing environment.

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.

This role works with sensitive content or situations and will be exposed to graphic, controversial, 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 diverse 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.

Responsibilities

  • Develop scalable safety solutions for Artificial Intelligence (AI) products across Google by leveraging advanced machine learning and AI techniques.
  • Apply statistical and data science methods to thoroughly examine Google's protection measures, uncover potential shortcomings, and develop actionable insights for continuous security enhancement.
  • Deliver business outcomes by crafting data stories for a variety of stakeholders, including executive leadership.
  • Develop automated data pipelines and self-service dashboards to provide insights at scale.
  • Work with sensitive content or situations and be exposed to graphic, controversial or upsetting topics or content.

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