Senior Research Data Scientist, Core Compute Analytics

Minimum qualifications:

• Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field or equivalent practical experience.
• 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

Core Compute Analytics is a team of data scientists and software engineers with the mission of improving the efficiency and performance of the ecosystem and of Google Cloud Platform.

In this role, you will build data pipelines to deliver production hints that improve efficiency and allow Google to achieve fleet-wide optimization goals and develop statistical modeling frameworks that allow Google to effectively manage its infrastructure spending. You will define compute telemetry needs and munge the data to strategically decide which projects infrastructure teams should pursue as they strive to enable new capabilities for Google. The current issues include increasing heterogeneity in the fleet arising from the end of Moore's law and the introduction of Machine Learning (ML) accelerators as well as the divergence between the efficiency goals of internal Google workloads and Google Cloud Platform.The US base salary range for this full-time position is $166,000-$244,000 + 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.

In this role, you will build data pipelines to deliver production hints that improve efficiency and allow Google to achieve fleet-wide optimization goals and develop statistical modeling frameworks that allow Google to effectively manage its infrastructure spending. You will define compute telemetry needs and munge the data to strategically decide which projects infrastructure teams should pursue as they strive to enable new capabilities for Google. The current issues include increasing heterogeneity in the fleet arising from the end of Moore's law and the introduction of Machine Learning (ML) accelerators as well as the divergence between the efficiency goals of internal Google workloads and Google Cloud Platform.
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

• Formulate and solve the statistical problems that arise from the large scale deployment of novel compute technologies.
• Present your results and recommendations to Engineering Leadership, helping them to understand the opportunity space and trade-offs.
• Have high visibility within the technology organization by partnering with teams throughout Technical Infrastructure, Google Cloud Platform, and Core Systems.
• Develop technical metrics, statistical models, simulation frameworks, data pipelines, and experiments.