Research Data Scientist, Cloud Product Analytics

Research Data Scientist, Cloud Product Analytics

Google Sunnyvale, CA, USA

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

Google Cloud Platform (GCP) offers a suite of products ranging from Compute to Storage and ML. Our Cloud Analytics team focuses on understanding platform resources to provide analytical insights, improve product excellence, and support scalable growth.

In this role, you will focus on product analytics for GCP's consumption products, such as Spot and Dynamic Workload Scheduler (DWS), analyzing and improving VM reliability to optimize overall resource usage and efficiency. You will also contribute to high‑visibility projects, working cross‑functionally with the Google Maps Platform (GMP) team on agent analytics while partnering with core engineering and product groups.

To achieve this, you will analyze complex system logs, define key performance and reliability metrics, and apply rigorous statistical methodologies to draw insights that guide infrastructure and engineering decisions.

Individual pay is determined by factors including job‑related skills, experience, and relevant education or training.

Responsibilities

• Lead analytics for cloud consumption products, such as Spot and DWS, focusing on improving VM reliability and optimizing resource efficiency.
• Collaborate on high‑visibility GMP initiatives, working cross‑functionally with the Google Maps Platform engineering and product teams to develop and enhance agent analytics.
• Analyze complex system logs and apply rigorous statistical methodologies and next‑generation AI technologies to extract insights.
• Establish core performance and reliability metrics to guide strategic infrastructure, product, and engineering decisions.

US: $ - $ (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.

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