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Note: By applying to this position you will have an opportunity to share your preferred working location from the following: New York, NY, USA; Mountain View, CA, USA.Minimum qualifications:
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
- 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.
- Experience with statistical data analysis such as linear models, multivariate analysis, stochastic models, and sampling methods.
- PhD degree in a Quantitative discipline.
- Experience with statistical data analysis such as linear models, multivariate analysis, stochastic models, sampling methods with machine learning on large datasets.
- Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data.
- Ability to select the right statistical tools to solve a data analysis problem.
- Ability to both teach others and learn new techniques such as differential privacy, with excellent leadership and self-initiation skills.
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
- Help suggest, support and shape new data-driven advertising and marketing products in collaboration with engineering, product and customer facing teams.
- Collaborate with teams to define relevant questions about advertising effectiveness, incrementality assessment, the impact of privacy, user behavior, brand building, targeting, bidding etc., and develop and implement quantitative methods to answer those questions.
- Find ways to combine experimentation, statistical-econometric, machine learning and social-science methods to answer business questions at scale.
- Use causal inference methods to design and suggest experiments and new ways to establish causality, assess attribution and answer strategic questions using data.
- Work with large, complex data sets. Solve difficult analysis problems, applying advanced analytical methods. Conduct end-to-end analyses that include data gathering and requirements specification, exploratory data analysis, model development, and written and oral delivery of results to business partners and executives.
Key Skills
Ranked by relevance
data analysis
machine learning
python
sql
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- Posted
- Nov 12, 2025
- Type
- Full-time
- Level
- Not Applicable
- Location
- New York
- Company
Industries
Information Services
Technology
Information
Internet
Categories
Information Technology
Engineering
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3 roles aligned with this opportunity
View Job Details
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Software Engineer III, YouTube Streaming Trust and Safety
2026-05-20
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Information Technology
View Job Details
Related
Software Engineering Manager, Geo
2026-05-26
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View Job Details
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Network Implementation Engineer II
2026-05-26
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