The Search Platform Data Science team at Google needs to understand and measure Search systems, including Experiment, Reliability, Velocity, Latency, Capacity, Content, Logs Quality, and Search Infrastructure. The role will partner with the Search Experiments Infrastructure team to support fast and measurable Search innovation with experimentation infrastructure, methodology, and tooling.
Requirements
- coding (e.g., Python, R, SQL)
- querying databases
- statistical analysis
- infrastructure innovation and experimentation methodology
- dig into complicated codebases to understand how Search systems work and drive fundamental changes
- using AI to assist with experiment design and analysis
- meta-analysis, experiment design and analysis, causal inference, etc.
Responsibilities
- Use custom data infrastructure or existing data models as appropriate, using specialized expertise.
- 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).
- Separately format, re-structure, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.
- Experience with infrastructure innovation and experimentation methodology, with a willingness to dig into complicated codebases to understand how Search systems work and drive fundamental changes.
- Experience using AI to assist with experiment design and analysis.
Other
- 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.
- 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.
- 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.
