Minimum qualifications:

• Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, a related quantitative field, or equivalent practical experience.
• 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:

• PhD in Statistics, Engineering, Physics, Mathematics, or a related 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 a PhD degree.

About the job

Google is and always will be an engineering company. We hire people with a broad set of technical skills who are ready to take on some of technology's greatest challenges and make an impact on millions, if not billions, of users. At Google, data scientists not only revolutionize search, they routinely work on massive scalability and storage solutions, large-scale applications and entirely new platforms for developers around the world. From Google Ads to Chrome, Android to YouTube, Social to Local, Google engineers are changing the world's one technological achievement after another.

Our team is committed to deliver globally optimal solutions that reduce infrastructure investments, operating costs and electricity-based CO2 emissions of Google’s fleet by optimizing network, compute, storage, power, and carbon together.

As a Data Scientist, you will evaluate and improve Google's products. You will collaborate with a multi-disciplinary team of engineers and analysts on a wide range of problems. You will bring scientific excellence and statistical methods to the challenges of product creation, development and improvement with an appreciation for the behaviors of the end user. You will use your energy domain knowledge and technical expertise to develop energy analytics solutions used for efficient, scalable, and carbon-aware management of Google scale energy assets.Our team is committed to deliver globally optimal solutions that reduce infrastructure investments, operating costs and electricity-based CO2 emissions of Google’s fleet by optimizing network, compute, storage, power, and carbon together.

As a Data Scientist, you will evaluate and improve Google's products. You will collaborate with a multi-disciplinary team of engineers and analysts on a wide range of problems. You will bring scientific excellence and statistical methods to the challenges of product creation, development and improvement with an appreciation for the behaviors of the end user. You will use your energy domain knowledge and technical expertise to develop energy analytics solutions used for efficient, scalable, and carbon-aware management of Google scale energy assets.
As a Data Scientist, you will evaluate and improve Google's products. You will collaborate with a multi-disciplinary team of engineers and analysts on a wide range of problems. You will bring scientific excellence and statistical methods to the challenges of product creation, development and improvement with an appreciation for the behaviors of the end user. You will use your energy domain knowledge and technical expertise to develop energy analytics solutions used for efficient, scalable, and carbon-aware management of Google scale energy assets.

Responsibilities

• Lead projects with energy system, market analysis and carbon impact analysis, modeling and optimization, drawing from multiple problem solving methods and energy domain expertise to choose the right tool and right level of complexity appropriate for the business challenges.
• Engage broadly with the organization to identify, prioritize, frame, and structure complex and ambiguous challenges arising in the energy domain, where advanced analytics projects or tools can have the biggest impact.
• Identify and communicate the challenges and opportunities that the group should be working on. Help define the problem solving 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. Translate analysis results into business recommendations.