Research Data Scientist, Magic Eye
Google· Internet & Cloud Services· Oct 16, 2026 · 12d ago
Mountain View, CA, USA
In office
Full-time
Mid
$117K–$176K est.
3+ years exp
Job description
Magic Eye's mission is to guide strategic decision making for Google's consumer products through data-informed insights, actionable user metrics, and definitions of success. The analysis team partners closely with cross-product area teams from Search, Ads, Android, YouTube, etc., and cross-functionally with teams from Engineering, Behavioral Economics, UX, Finance to bring methodology, data, and insights to Googlers and Google leads.
The analysis team is focused on cross-product user research and metric development to dig into Google's performance, including understanding Google's most important users, drivers of key trends, and layering in context from industry and the world. Key research questions include understanding the rapidly evolving GenAI landscape and user journeys across products and devices to identify cross-company strategic opportunities. This team also focuses on advanced decision making frameworks and tooling, ranging from observational, to causal inference, to experiments. We're all about scale to develop and leverage reliable, reproducible analyses for ourselves, our partners, and to drive aligned decision making across Google.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google .
• Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer.
• 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.
• Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure.
• 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.
• Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.
• Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
• 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
Minimum qualifications:
• Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
• 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
Preferred qualifications:
• 5 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
Application prep
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Keywords to mirror
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- Platform
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