Senior Research Data Scientist, Network and Machines Optimization, Cloud

Senior Research Data Scientist, Network and Machines Optimization, Cloud

Google Sunnyvale, CA, USA

Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.

• 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.
• 4 years of experience in data analysis or related fields as a Statistician, Data Scientist, etc.
• Experience with statistical software (e.g., R, Python, MATLAB, pandas) and database languages (e.g., SQL).

• PhD degree in Data Science, Operations Research, Industrial Engineering, Statistics, or related quantitative field.
• 4 years of relevant work experience (e.g., as a data scientist), including experience applying advanced analytics to planning and infrastructure problems.
• Experience working on technical infrastructure for cloud computing with designing and building supply chain models.
• Experience in problem-framing, designing and building time-series forecasting, optimization, simulation, cost-tradeoff and probabilistic decision‑making models.
• Excellent problem‑solving, project management skills with customer service and team collaboration skills.

Operations and Infrastructure Data Science is a team of Data Science (Analyst and Research) experts, who provide model‑based decision support to scale Google’s Technical Infrastructure optimally.

The AI and Infrastructure team builds and maintains the architecture, from data centers to next‑generation platforms, making Google’s product portfolio possible.

As a Data Scientist, you will enable Google to deliver AI and Infrastructure with unparalleled scale, efficiency, reliability, and velocity which involves developing critical forecasting and capacity planning tools for Google’s technical infrastructure. You will apply investigative methods including forecasting, simulation, probabilistic cost‑tradeoffs, and operations research to solve issues across Google’s internal services, Google Cloud Platform, and the hardware supply chain.

Your role includes planning the machine learning, compute, and storage machines that serve Google and its customers.

Our mission: “Drive optimal capacity planning for machines and cluster networking by providing forecasts, models, policies, metrics and insights.” You must think critically and strategically about Google’s cloud and AI as a technology, a business, and an operation. You will interface with hardware engineers on total cost of ownership, software engineers on resource optimization, and operations executives on fleet plans, all based on your analytical models.

You will be leveraging data, advanced analytics, and strategic forecasting to optimize large‑scale investments in technical infrastructure.

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.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents‑to‑be, criminal histories consistent with legal requirements, or any other basis protected by law.

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