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Senior Data Scientist
GoogleSunnyvale, CA, USASenior$206,600 - $237,0003+ years
Apply Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.
Minimum qualifications:
- Bachelor’s degree in Data Science, Statistics, Mathematics, Physics, Economics, Operations Research or a related field and 6 years of progressive post-baccalaureate experience in the job offered or in a Data Scientist-related occupation.
- Alternatively, will accept a Master’s degree in Data Science, Statistics, Mathematics, Physics, Economics, Operations Research or a related field, and 3 years of experience in the job offered or in a Data Scientist-related occupation.
- Position requires 3 years of experience in the following: Coding in SQL, Python, or R to manipulate, analyze, visualize large datasets, and build models; Statistical analysis or quantitative data synthesis to draw inferences, identify trends, and solve product or business problems; User experience measurement or attribution modeling to evaluate customer interactions; Product analytics or business intelligence to define metrics, create dashboards, and measure success; and Stakeholder management or cross-functional collaboration to align objectives, gather consensus, and persuade leaders.
About the job
The US base salary range for this full-time position is $206,600 - $237,000+ 15% bonus target + equity + benefits determined by role, level, and location. Individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Learn more about benefits at Google.
Position reports to the Google San Francisco, CA office & may allow for a hybrid schedule as per Google policy.
Responsibilities
- Extract, format, and validate complex datasets from multiple sources to guarantee quality and analysis readiness.
- Execute advanced analyses utilizing SQL, R, and Python to resolve ambiguous problems and deliver optimal solutions.
- Report Key Performance Indicators to leadership and translate analytical results into actionable product improvement insights.
- Prototype scalable business cases and build robust processes with the foresight to anticipate future challenges.
- Master internal data structures and metrics to effectively advocate for impactful product development changes. Influence cross-functional teams to align strategic resources while providing oversight and setting standards for data scientists.
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