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Minimum qualifications:
As a key member of the team, you work with engineers to analyze and interpret data, develop metrics to measure results and integrate new methodologies into existing systems.
As member of the Resource Efficiency Data Science team, you will apply operations research and statistical methods to solve challenges related to compute, storage, network, and data center capacity for Google’s internal services and Google Cloud Platform. You will work across Google’s Platforms Engineering, Systems Infrastructure, and Site Reliability Engineering teams to optimize our deployment of resources and drive innovation in our software stack, allowing for efficient use of resources.
As a Senior Data Scientist, you will think about Google’s cloud as a technology, a business, and as an operation. You will be comfortable discussing total cost of management with hardware engineers, resource optimization with software engineers, or reviewing fleet plans and deployment policies with operations executives, all based upon the analytical models that you will be developing.Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.
Responsibilities
- Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, a related quantitative field, or equivalent practical experience.
- 5 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of experience with a PhD degree.
- Experience with statistical data analysis and experimental design.
- 8 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of experience with a PhD degree.
- 4 years of experience as a data scientist, including applying advanced analytics to planning and infrastructure problems.
- Experience designing and building machine learning models.
- Experience with optimization models.
- Excellent problem-framing, problem-solving and project management skills.
As a key member of the team, you work with engineers to analyze and interpret data, develop metrics to measure results and integrate new methodologies into existing systems.
As member of the Resource Efficiency Data Science team, you will apply operations research and statistical methods to solve challenges related to compute, storage, network, and data center capacity for Google’s internal services and Google Cloud Platform. You will work across Google’s Platforms Engineering, Systems Infrastructure, and Site Reliability Engineering teams to optimize our deployment of resources and drive innovation in our software stack, allowing for efficient use of resources.
As a Senior Data Scientist, you will think about Google’s cloud as a technology, a business, and as an operation. You will be comfortable discussing total cost of management with hardware engineers, resource optimization with software engineers, or reviewing fleet plans and deployment policies with operations executives, all based upon the analytical models that you will be developing.Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.
Responsibilities
- Develop, maintain, support, and enhance custom forecasting and capacity planning tools for Google Product Area resource planning.
- Lead projects with analysis and modeling, drawing from multiple methods to choose the right tool and right level of complexity appropriate for the business challenges.
- Engage with the organization to identify, prioritize, frame, and structure challenges, where advanced analytics projects or tools can have the biggest impact.
- Help define the direction and influence the direction of the associated engineering and infrastructure work.
- Articulate business questions and use mathematical techniques to arrive at an answer using data and translate analysis results into business recommendations.
Key Skills
Ranked by relevance
python
cloud
sql
google cloud platform
machine learning
data analysis
storage
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- Posted
- Jul 04, 2025
- Type
- Full-time
- Level
- Mid-Senior
- Location
- Warsaw
- Company
Industries
Information Services
Technology
Information
Internet
Categories
Information Technology
Engineering
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3 roles aligned with this opportunity
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