Trust & Safety ML Analyst, Google Workspace
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Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 5 years of experience managing projects and defining project scope, goals, and deliverables.
- 5 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.
Preferred qualifications:
- Master's degree or PhD in Computer Science, Statistics, Mathematics, or Operations Research.
- 5 years of experience in roles related to business analysis, statistical analysis and Machine Learning.
- Ability to solve unstructured business problems in fraud investigations and a risk management space.
- Excellent process/project management, prioritization, analytical, problem-solving, and multitasking skills, with the ability to process data to drive business strategies and decisions.
- Experience in building, analyzing and maintaining ML / AI models.
About the job
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
- Work with unstructured data sets to get insights and develop solutions on non-compliant inventory, conduct data analyses and identify opportunities for new signals and drive the utilization of these new signals to completion.
- Build and evaluate models that automate decision-making or generate leads for content review teams.
- Work cross-functionally with Product, Engineering, and other enforcement teams within Trust and Safety to push for policy changes and resolve product vulnerabilities
- Drive strategy and team focus on using data mining and analysis techniques to provide insights on abuse and operational trends.
- Develop and analyze production ML models to ensure high quality performance.
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