Senior Data Scientist, Research, Operations Data Science

Minimum qualifications:

• Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, 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.
• Experience in designing and building optimization, simulation, and probabilistic decision-making models.
• Experience in designing and building statistical models or physical models for energy consumption.
• Experience in the computer hardware industry.

About the job

Operations Data Science (ODS) is a team of Data Science and Business Analysis experts, who provide model-based decision support to scale Google's Technical Infrastructure optimally.

In this role, you will lead data modeling and estimation efforts for our Google Cloud Carbon Footprint product. You will collaborate with internal teams to gather, analyze, and interpret data related to Google Cloud software usage, resource consumption, energy consumption, and carbon emissions. You will work to enhance the value of the Google Cloud Carbon Footprint by more accurately estimating the energy consumption and carbon emissions of customers' workloads and projects. You will build problem-solving tools to clearly identify energy and carbon-savings opportunities for customers. Additionally, you will quantify the opportunity size of potential Cloud carbon-efficiency projects and prioritize these to build Cloud features that help customers reduce their emissions.

The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.

We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

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

• Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.
  
• Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure.
  
• Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Format, re-structure, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.
  
• Collaborate with subject matter experts to combine hardware insights with energy and emissions data to prioritize carbon-reduction efforts in Cloud.
• Develop, maintain, support, and enhance models and estimation tools for the energy-use and carbon-footprint of Google Cloud customer workloads.