Senior Product Data Scientist, Devices Insights and Analytics

Google•Mountain View, CA

About The Position

We are the Devices Insights and Analytics team and are part of the Platform and Devices Product Area. Our mission is to be a true insights and investigative source of engaged advantage to our product area. We inspire and deliver action for our products and business with the customer at the center. We are positioned to drive customer centricity at the intersection of business and customer needs. In this role, you will work closely with executive leaders, product managers, and others, and our unique contribution is combining with analytics and data.

Requirements

Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
8 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 5 years of experience with a Master's degree.
Experience with causal inference analysis.

Nice To Haves

Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
Experience with Large Language Models.

Responsibilities

Perform analysis utilizing relevant tools (e.g., SQL, R, Python), and help solve problems, narrowing down multiple options into the best approach, and take ownership of open-ended ambiguous business problems to reach an optimal solution.
Build new processes, procedures, methods, tests, and components with foresight to anticipate and address future issues.
Report on Key Performance Indicators (KPIs) to support business reviews with the cross-functional/organizational leadership team, and translate analysis results to business insights or product improvement opportunities.
Build and prototype analysis and business cases iteratively to provide insights at scale, and develop comprehensive knowledge of Google data structures and metrics, advocating for changes where needed for product development.
Apply Large Language and other Machine Learning models to analyze structured and unstructured data.