Senior Data Scientist, Research, Global Networking and Infrastructure

About the position

Google Global Networking and Infrastructure (GGN&I) builds and operates Google's private backbone, a global fiber network linking data centers and powering all Google services. The GGNI Data Science team applies expertise in statistics, operations research, economics, and computing to optimize the design, construction, and performance of this network. 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 one technological achievement after another. 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 issues of product creation, development and improvement with an appreciation for the behaviors of the end user.

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.
• Use custom data infrastructure or existing data models as appropriate, using specialized knowledge. Design and evaluate models to mathematically express and solve defined problems with limited precedent.
• 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.
• Develop models and analysis using Python, R, SQL, and shell scripts. The output will typically be a document with useful findings or prototype production code.
• Work with engineers to refine analysis and implement prototypes.

Requirements

• 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.
• Experience in Python or R for data analysis and modeling.
• Experience with shell scripting.

Nice-to-haves

• 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.

Benefits

• The US base salary range for this full-time position is $166,000-$244,000 + bonus + equity + benefits.