Search Quality Analyst

About the job

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.

The US base salary range for this full-time position is $110,400 - $153,000 + 15% bonus target + equity + benefits determined by role, level, and location. Individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Learn more about benefits at Google.

Position reports to the Google office & may allow for a hybrid schedule as per Google policy.

Responsibilities

• Analyze complex problems using data and statistical methods to identify and prevent fraud.
• Improve tools and automated systems through technical analysis and present findings to stakeholders.
• Generate and test hypotheses to define quantitative metrics that drive logical decision-making.
• Construct accurate queries to interpret data and communicate insights to diverse audiences.
• Identify meaningful signals and behavioral patterns to improve algorithms and address system gaps. Compute statistics to evaluate the performance of complex technical models and classifiers.

Qualifications

Minimum qualifications:

• Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field and 2 years of experience in the job offered or in a Search Quality Analyst-related occupation.
• Position requires 2 years of experience in the following: Data synthesis for solution generation and action planning; Automated system improvement through data analysis; High-volume product data extraction and manipulation; SQL and R or Python for data analysis; and Product abuse technique and practice analysis.