Job Overview
Role: Engineering Analyst, Trust and Safety, YouTube Location: Hyderabad Experience: 1+ Year Qualification: B.E/B.Tech/M.E/M.Tech Key Skills: Data Analysis, Project Management, SQL, Python, C++
Job Description
In this role, you will perform fraud and spam investigations using multiple data sources, identify product vulnerabilities, and drive anti-abuse experiments to prevent abuse on YouTube. You will work with engineers and cross-functional stakeholders to improve workflows through process enhancements, automation, and anti-abuse system creation. Responsibilities also include designing and refining prompts for Large Language Models (LLMs) to improve accuracy in identifying abusive content, applying advanced statistical methods to understand abuse impact, and contributing to new workflow strategies. This position requires on-call weekend work on a rotational basis and exposure to graphic or controversial content.
Roles and Responsibilities
- Fraud & Spam Investigations: Perform fraud and spam investigations using multiple data sources, identify product vulnerabilities and drive anti-abuse experiments to prevent abuse.
- Workflow Improvement: Work with engineers and interact cross-functionally with stakeholders to improve workflows by process improvements, automation and anti-abuse system creation.
- LLM Prompt Engineering: Design and refine prompts for Large Language Models (LLMs) to improve their accuracy in identifying and classifying abusive content and behavior, including prompt engineering, data labeling, and performance analysis.
- Statistical Analysis: Apply advanced statistical methods to datasets to understand the impact of abuse to the YouTube ecosystem.
- Strategy & Development: Contribute strategy and development of new workflows.
- Technical Learning: Learn technical concepts and systems and deliver results using them.
- Quality Maintenance: Maintain and promote quality by providing regular feedback metrics to the Global team.
- Technological Solutions: Manage technological solutions for streamlining quality assurance and produce training solutions.
Skills and Eligibility Criteria
Educational Background: Bachelor’s degree or equivalent practical experience. Master’s degree in a quantitative discipline is preferred.
Experience: 1 year of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data. 1 year of experience in managing projects and defining project scope, goals, and deliverables.
Mandatory Technical Skills:
- SQL
- R
- Python
- C++
Competencies:
- Machine Learning: 1 year of experience with machine learning systems (Preferred).
- Data Management: Experience with collecting, managing and synthesizing datasets and information from disparate sources, statistical modeling, data mining and data analysis, and with metrics analysis, experiment design and automation (Preferred).
- Communication: Excellent communication skills (Preferred).