Data Scientist

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 $174,550 - $211,000 + 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 San Bruno, CA office & may allow for a hybrid schedule per Google policy.

Responsibilities:

• Collaborate with stakeholders to translate business needs into clear analytical questions, evaluation metrics, and mathematical models.
• Gather business goals, organizational context, and information regarding existing and upcoming data infrastructure to guide your analysis.
• Extract and compile large-scale data from multiple sources using tools such as SQL, R, and Python.
• Validate and prepare datasets for analysis by formatting, re-structuring, and ensuring data quality and integrity.
• Design and evaluate sophisticated models to mathematically solve complex problems with limited precedent. Apply scientific and statistical methods to evaluate and improve Google's products for millions of users worldwide.

Minimum qualifications:

• Master’s degree in Computer Science, Statistics, Mathematics, Data Science, Economics, Physics, Operations Research, or a related field and 3 years of experience in the job offered or in a Data Scientist-related occupation.
• Alternatively, will accept a Ph.D. in Computer Science, Statistics, Mathematics, Data Science, Economics, Physics, Operations Research, or a related field.
• Position requires: Developing metrics and analyzing data to support strategic decisions; Building statistical machine learning models for both offline analysis and production-scale applications; research new methods for experimentation and statistical inference; Python or R for statistical analysis and algorithms; SQL for querying databases; and Presenting analyses and visualizing data from experiments, forecasting, and model prediction.