Requirements:

Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
3 years of work 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 work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
2 years of work experience in data science or quantitative analytics with focus on statistical modeling, machine learning, and visualization.
Experience, education/training, or demonstrated interest in machine learning.
Excellent problem-solving skills and business judgment, articulating product questions, pulling data from datasets (SQL, BigQuery or equivalent technologies).
Excellent written and verbal communication skills and ability of translating analysis results into business recommendations.

Leverage advanced statistical methods on massive datasets to extract insights.
Use custom data infrastructure or existing data models to design models and automate solutions.
Analyze product and platform usage patterns to inform strategy and engineering decisions.
Collaborate with stakeholders to identify business questions and provide data-driven insights.

Opportunity to work with various teams within Chrome and impact billions of users.
Contribute to evolving Chrome into a more personalized and helpful user agent.
Work on an adopted product, influencing product and engineering directions.
Equal employment opportunity regardless of various factors; see Google's EEO policy for more details.