Engineering Analyst, Trust and Safety Monetization
Teknik, data och digitalt · Data, AI och analys · Dataanalys · Maskininlärning · Mjukvaruutveckling
I korthet
Our team builds a safe ads ecosystem for publishers, advertisers, and end-users by defending Google's ad products from fraud and abuse. We analyze millions of publishers and billions of events to stop bad actors. As an Engineering Analyst, you will perform data analysis, drive projects, and partner with engineering teams to improve ad traffic infrastructure and defense systems.
Ansvarsområden
- Perform analysis and investigations using a variety of data sources and take enforcement actions to identify and defend novel fraud and abuse on Google's ad products.
- Partner closely with Engineering teams to improve ad traffic infrastructure, defense systems, and workflows.
- Proactively identify and help implement efficiency improvements through advanced machine learning techniques, scaled defenses, and automation.
- Drive full lifecycle projects across Product, Engineering, and Trust and Safety teams to prevent abuse by improving policies and closing product vulnerabilities.
- Work collaboratively with team mates around the globe and deliver projects from beginning to end in a timely manner.
- Be able to review or be exposed to sensitive content.
Krav
- 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.
Önskade kvalifikationer
- Master's degree in a quantitative discipline.
- 2 years of experience with one or more of the following languages: SQL, R, Python, or C++.
- Knowledge of one or more of the following areas: statistical analysis and Machine Learning libraries (e.g., R, Scikit-learn), programming languages (e.g., Python, C/C++), Large Language Models (LLMs) or Generative AI.
#trust and safety#monetization#fraud detection#abuse prevention#ad products#data analysis#machine learning#project management