Staff Data Scientist, Research, Search Platforms

Minimum qualifications:

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

Preferred qualifications:

• 10 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of work experience with a PhD degree.
• PhD in a quantitative discipline such as Statistics, Engineering, Physics or Mathematics.
• Experience articulating business questions and using mathematical techniques to arrive at an answer using available data and translating analysis results into business recommendations.
• Ability to exhibit leadership and self-direction, along with a proactive willingness to both instruct and learn new techniques.

About the job

In this role, you will work on understanding and measuring Search systems, including but not limited to Experiment, Reliability, Velocity, Latency, Capacity, Content and Ecosystem, Logs Quality and Search Infrastructure. You will focus on understanding and measuring Search systems. You will work on defining and developing the system metrics that would let us understand how effective and efficient our systems are, and how they interact with each other (and other Google systems). You will also partner with engineering and product teams in Search Platforms on system-level optimizations, and collaborate closely with Search verticals and horizontal teams, Site Reliability Engineers (SREs), Core to understand the impact of system changes on user experience and on Google business.In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.
The US base salary range for this full-time position is $197,000-$291,000 + 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.
The US base salary range for this full-time position is $197,000-$291,000 + 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

• Work with large data sets to solve difficult, non-routine analysis problems using advanced investigative methods. Conduct analysis, from data gathering to presentations.
• Build and prototype analysis pipelines for scalable insights. Develop an understanding of Google data structures and metrics, advocating for changes to support product development and business.
• Interact cross-functionally with teams and individuals. Collaborate closely with engineers to identify, design, and assess improvements for Google products.
• Make business recommendations through effective presentations to stakeholders, leveraging visual displays of quantitative information for cost-benefit, forecasting, and experiment analysis.
• Research and develop analysis, forecasting, and optimization methods to enhance Google's user-facing products, including areas like ads and search quality, user behavioral modeling, and live experiments.