Description

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.
• 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.
• Excellent technical skills on meta-analysis, experiment design and analysis, causal inference, etc.

About the job
Search Platform Data Science team works on understanding and measuring Search systems, including but not limited to Experiment, Reliability, Velocity, Latency, Capacity, Content, Logs Quality and Search Infrastructure.

In this role, you will partner closely with the Search Experiments Infrastructure team to support fast and measurable Search innovation with experimentation infrastructure, methodology, and tooling.
The US base salary range for this full-time position is $141,000-$202,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or 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 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.
  

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Requisition #: 101033997668098758

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