Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
  
• 1 year of experience in data management, metrics analysis, experiment design and automation.
  
• Experience with classification systems, ranking systems, or similar.
  

Preferred qualifications:

• Experience translating analytical insights into business strategies and actions.
  
• Experience creating opportunities to innovate, conceptualize, and complete while working with global teams.
  
• Experience collecting, managing, and synthesizing large data sets and information from disparate sources, statistical modeling, data mining and data analysis.
  

About the job

As an Engagement Abuse Analyst, you will be a key contributor to the strategy for reducing network badness on YouTube. You will balance the short-term requirements and see the big picture to make long-term recommendations accordingly. You will be exposed to graphic, controversial, and sometimes offensive video content during team escalations in line with YouTube's community guidelines. You will work on-call at weekends on a rotational basis as needed.

At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we listen, share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of cutting-edge technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun - and we do it all together.

Responsibilities

• Apply advanced methods to data sets in understanding the impact of abuse to the YouTube ecosystem. Develop new workflows against known vectors of abuse.
• Learn technical concepts, systems, and deliver meaningful results using them. Communicate technical results and methods clearly.
  
• Maintain quality by providing feedback metrics to the Global team. Manage technological solutions for streamlining quality assurance and produce scalable training solutions to emergent workflows.
  
• Perform fraud and spam investigations using various data sources, identify product vulnerabilities, and drive anti-abuse experiments to prevent abuse. Work with engineers and interact cross-functionally with stakeholders to improve workflows via process improvements, automation, and anti-abuse system creation.
  
• Develop Machine Learning Models (e.g., using LLMs, BERT) to detect and prevent various types of abuse on YouTube. Develop Machine Learning based detection systems for different adversarial and large-scale coordinated abuse vectors