Data Scientist, Research, Core Compute Analytics
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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
Core Compute Analytics is a team of data scientists and software engineers with the mission of improving the efficiency and performance of Google’s infrastructure, for both traditional compute and the fast emerging Machine Learning (ML) fleet across Borg and Google Compute Engine (GCE). We collaborate closely with Core Infrastructure and Google Cloud Platform (GCP) teams to solve problems and support decision-making across different layers of the compute stack. We build data pipelines to deliver production hints that enhance efficiency and allow Google to achieve fleet-wide optimization goals. We develop statistical modeling frameworks that allow Google to effectively manage its infrastructure spending. We define compute telemetry needs and manage the data to plan which projects infrastructure teams should pursue as they strive to enable new capabilities for Google.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.
Responsibilities
- Work with engineering and product teams to enable insights and data-driven decision making for improving efficiency and performance of both Google’s traditional and ML compute infrastructure.
- Work with a large data set to perform end-to-end analysis such as identifying or understanding important business problems, translating to tractable data science questions, processing data and performing analysis, and communicating results to stakeholders to inform product directions
- Provide leadership and identify new areas where data science can play a significant role in shaping the next generation of Google’s compute infrastructure.
- Lead initiatives to enhance the data, tools and methodology, beyond the scope of a single product application, to help scale the team's work.
- Interact cross-functionally and cultivate partnerships with a wide variety of teams including engineering, operations, product, and Data Scientist (DS) teams to identify opportunities for analysis.
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