Staff Data Scientist, Research, Applied Research

About the position

In this role, you will play a pivotal role in developing the metrics, methodologies and tools. You will have technical expertise and innovation to foster developments in Search and Commerce. In Google Search, we're reimagining what it means to search for information - any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.

Responsibilities

• Collaborate with stakeholders in cross-projects 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 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). Separately format, re-structure, 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 or equivalent practical experience.
• 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.
• 3 years of work experience in end-user facing experimentation design.

Nice-to-haves

• 10 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of work experience with a PhD degree.

Benefits

• Bonus
• Equity
• Benefits