Staff Data Scientist, Applied Research, Search Platforms
Job Summary
Job Description
- Master's degree in quantitative field
- 8+ years experience in analytics
- Proficiency in Python, R, SQL
- Experience with statistical modeling
- Excellent communication skills
- PhD degree
- Experience with strategic analysis
- Experience with executive presentations
- Experience with survey design
- Bonus
- Equity
- Benefits
10 skills required
Job Details
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.
- Experience with strategic analysis, metric reporting, and executive presentations.
- Experience with statistical modeling, survey design, data analysis, and effective experimental design.
- Ability to complete project work separately and work with cross-functional teams in a dynamic, fast-moving environment.
- Ability to apply statistical training to real-world data.
- Excellent communication skills, with the ability to extract insights from data and telling convincing stories.
About the job
Search Platform Data Science team works on understanding and measuring Search systems, including but not limited to Experiment, Reliability, Velocity, Latency, Capacity, Content, Logs Quality and Search Infrastructure.
Search Platforms Data Science team focuses on understanding and measuring Search systems. Data Scientists in Search Platforms 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). The team partners with Engineering and Product teams in Search Platforms on system-level optimizations, and collaborates closely with Search verticals and horizontal teams, 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 .
Responsibilities
- Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced problem solving methods. Conduct analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
- Build and prototype analysis pipelines iteratively to provide insights at scale. Develop a comprehensive understanding of Google data structures and metrics, advocating for changes where needed for both product development.
- Interact cross-functionally with a wide variety of people and teams. Work closely with engineers to identify opportunities for, design, and assess improvements to google products.
- Make business recommendations with effective presentations of findings at multiple levels of stakeholders through visual displays of quantitative information.
- Research and develop analysis, forecasting, and optimization methods to improve the quality of Google's user-facing products. Application areas include ads quality, search quality, end-user behavioral modeling, and live experiments.
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