Research Data Scientist, Core Metrics

Google•Mountain View, CA

13d•$147,000 - $210,000

About The Position

Ads Metrics is the Data Science team for Search ads. The team supports the SAGE (Search Ads and Google Experience) organization in developing Google ad products, including text ads, shopping ads, and Discovery ads. These products contribute more than $1 billion in annual revenue and are complex, advanced, and rapidly evolving. The role uses analytics and data science to address product and business questions, design and evaluate models, and prepare data for analysis. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

Requirements

Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
At least 3 years of work experience using analytics to solve product or business problems, coding (for example, Python, R, or SQL), querying databases, or conducting statistical analysis; alternatively, a PhD degree.

Nice To Haves

5 years of work experience using analytics to solve product or business problems, coding (for example, Python, R, or SQL), querying databases, or conducting statistical analysis; alternatively, a PhD degree.

Responsibilities

Collaborate with stakeholders across projects and teams to identify and clarify business or product questions; provide feedback to turn questions into tractable analyses, evaluation metrics, or mathematical models.
Use custom data infrastructure or existing data models as appropriate, applying specialized knowledge to design and evaluate models that mathematically express and solve defined problems with limited precedent.
Gather information about the questions to answer, business goals, priorities, organizational context, and existing or upcoming data infrastructure.
Own gathering, extracting, and compiling data across sources using relevant tools such as SQL, R, and Python.
Independently format, restructure, and validate data to ensure quality, and review datasets to ensure they are ready for analysis.