Data Scientist, Research Operations
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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.
About the job
The Optimally scale Data centers and Systems (ODS) is a team of Data Scientists (Research and Analyst) experts, who provide model-based decision support to scale Google's Technical Infrastructure optimally.If you like using data, metrics, forecasts, statistics, operations research, analytical insights, thinking, and executive-level business communications to optimize large dollar spend decisions on Google's Technical Infrastructure, then you should consider joining Optimally scale Data centers and Systems (ODS) as a Data Scientist.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.
Responsibilities
- Develop, maintain, support, and enhance custom forecasting and capacity planning tools for Google’s Data center infrastructure.
- Drive analysis and modeling, drawing from multiple analytical methods and choose the right method and level of complexity appropriate for the business issues.
- Engage broadly to identify, prioritize, frame, and structure complex and ambiguous issues, where data science projects or tools can have the biggest impact. Articulate business questions and use mathematical techniques to arrive at an answer using data.
- Translate analysis results into actionable business recommendations supported by technical documentation and presentations. Collaborate with cross-functional stakeholders to understand their business needs and frame analytical problems.
- Measure business outcomes driven from the analytical recommendations. Identify and communicate the issues, opportunities, and automation that the group should be working on.
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