Research Data Scientist, YouTube Search

About the position

Despite being used over one billion times per day, YouTube Search has only been recently explored from a data science perspective. There is quite a bit of unexplored territory where we can define foundational concepts with large scale impact and leverage. In this role, you will be the first go-to analyst to work on Search Verticals. Search Verticals is a full-stack area, and you will leverage your skills across multiple core competencies, such as ML classifier development, ranking, and experiments, to understand and optimize the YouTube Search Vertical experience. 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

• Collaborate with stakeholders in cross-project and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.
• Use custom data infrastructure or existing data models as appropriate, using specialized knowledge. Design and evaluate models to mathematically express and solve defined problems with limited precedent.
• Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure.
• Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Independently format, re-structure, and/or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.

Requirements

• Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
• 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.

Nice-to-haves

• 5 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
• PhD degree in Statistics, Data Science, Machine Learning, or Physics, or 3 years of work experience.

Benefits

• Bonus
• Equity
• Benefits