Requirements:

Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, a related quantitative field, or equivalent practical experience.
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 3 years of work experience with a PhD degree.

Nice to haves:

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.
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 communication skills and ability to translate analysis results into business recommendations.
Distinctive problem solving skills and impeccable business judgment. Good at articulating product questions, pulling data from large datasets (e.g., SQL, BigQuery or equivalent technologies).

Leverage advanced statistical methods on massive, complex datasets to extract insights from billions of events and thousands of features across different organizational sources.
Develop and deploy automated solutions, ranging from SQL query automation to real-time Python classification and ML modeling, to address key strategic challenges.
Analyze intricate product and platform usage patterns, translating data-driven insights into actionable product strategy and engineering decisions.
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 specialized knowledge. Design and evaluate models to mathematically express and solve defined problems with limited precedent.

Opportunity to work with billions of users on a high-impact product like Chrome.
Work within a Data Science Team that blends research and product expertise to address complex challenges.
Contribute to evolving Chrome and enhancing user experiences through data-informed insights.
Play a vital role in integrating Google's technology into Chrome to meet user needs.
Contribute to building a better, more open web with a focus on speed, simplicity, and security.