Data Scientist, Chrome, Research

Minimum qualifications:

• 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.
  

Preferred qualifications:

• 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.
  

About the job:

Chrome’s mission is to make the web work better for you. We do this by evolving Chrome, which serves the world and Google as both a product (4 billion plus clients) and a platform (that is: Chromium and related components that advance the open web and open media technologies). Your work will have tremendous impact throughout Chrome, as you have an opportunity to work with the many teams that use our systems to gate features and understand users.

As a platform, Chrome envisions a fast, safe, capable platform and thriving web for generations of users and developers. As a product, Chrome imagines a more helpful, adaptive agent that helps people with their multifaceted needs. Chrome's goal is to redefine browsing by delivering unparalleled safety, speed, efficiency, and ease of use, and integrating with Generative Artificial Intelligence (GenAI) and Google's web products, to understand user needs and provide personalized experiences.

In this role, you will blend research and product expertise to manage issues. You will leverage a mix of theoretical and practical knowledge in advanced statistical and machine learning (ML) techniques, predictive modeling, human evaluation, experimentation, forecasting, exploratory analysis, and more to drive data-informed innovation, unlock opportunities, and enhance user experiences within Chrome.

Responsibilities:

• Leverage advanced statistical methods on massive, complex datasets to extract insights from billions of events and thousands of features across organizational sources.
• 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.
• Navigate technical or methodological conversations and narrative-telling presentations. Make clear, concise product and engineering recommendations to drive major impact. Use coding and methodology.
• Demonstrate an interest and aptitude in data, metrics, analysis, and trends, and applied knowledge of measurement, statistics, and program evaluation.