Senior Data Scientist, Google Global Networking and Infrastructure
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Minimum qualifications:
- Master's degree in Statistics, Computer Science, Network Engineering, Economics, Mathematics, Operations Research, or a related technical field.
- 5 years in Data Science or Software Engineering, with a background in data modeling and analysis.
- Experience with agile software development and code review processes.
- Experience with shell scripting.
Preferred qualifications:
- PhD in Statistics, Computer Science, Network Engineering, Economics, Mathematics, Operations Research, or a related technical field.
- Experience as a Data Scientist working on infrastructure-related projects, with the ability to apply data science techniques to optimize and innovate within infrastructure systems.
- Experience with machine learning model deployment and C++ .
- Experience in computer programming and technical modeling through relevant side projects.
- Understanding of networking and data center infrastructure, with the ability to quickly learn and apply technical concepts related to network operations and planning.
About the job
Google Global Networking and Infrastructure (GGN&I) is a planet-scale system of high-capacity fiber optic cables that encircle the globe connecting data centers to each other and to users. We bring together experts who design, develop, build, and operate this network—the world’s largest and fastest. Our network is essential societal infrastructure, supporting all Google employees and product areas—including Search, YouTube, Workspace, Ads, Bets, and Cloud—and their customers worldwide. The GGN Data Science Team partners with organizations to enhance efficiency and drive strategic initiatives. We use our expertise in statistics, operations research, economics, computing, and machine learning to generate data-driven insights that improve the performance, reliability, and cost-effectiveness of the network.The Senior Data Scientist role in the GGN Data Science team is a highly technical position that bridges the gap between data science and networking infrastructure. In this role, you will optimize Google's network by applying modeling techniques and data analysis to address planning and operational challenges. Your work will directly influence strategic decisions related to network capacity, efficiency, cost management, and reliability.
You will partner with engineers, finance, operations, planning, routing, and other teams. You will transform data insights into actionable projects and implement solutions that integrate seamlessly into Google’s global infrastructure. You will be passionate about networking and infrastructure data science, adept at handling large datasets, and skilled in communicating technical concepts to diverse stakeholders. Additionally, you will contribute to the growth and development of the team by mentoring junior members and participating in the recruitment process.The US base salary range for this full-time position is $150,000-$223,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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.
Responsibilities
- Engage with internal partners to brainstorm project opportunities that align with the organization's goals.
- Develop and execute data-driven projects through analysis and modeling, using tools such as Python, R, SQL, and shell scripting.
- Work with engineers and technical program managers to implement changes based on findings.
- Communicate insights and recommendations to stakeholders through documentation and presentations. Ensure findings are integrated into business decisions.
- Educate the GGN Data Science team on your work. Mentor colleagues and interns. Foster a collaborative and growth-oriented team environment.
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