- Mountain View, CA
- Full-Time
- 7 days ago
Senior Research Data Scientist, Search Ads.
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Senior Research Data Scientist, Search Ads: our view in 3 lines...
- The Role:This role is for a senior data scientist focused on research and analysis for search ads and user interface improvements.
- The Person:The person will answer business and product questions, build and evaluate models, gather and validate data, and use SQL, R and Python to prepare datasets for analysis.
- Requirements:The ideal candidate has a master's degree in a quantitative field and experience using analytics, coding with Python, R and SQL, querying databases, and statistical analysis.
About the role
Minimum qualifications:
- Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
- 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.
Preferred qualifications:
- 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.
About the job:
Our team provides the critical analysis and data insights that guide our AdsUI partners in improving user interfaces, ad formats, and the overall search page experience. We are the premier team driving a $2XXB business, offering you the unique opportunity to land immediate, visible impact on billions of users worldwide—including yourself.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities:
- 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.
- Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure.
- Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Format, re-structure, and/or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.
