Minimum qualifications:
- Master's degree in Statistics or Economics, a related field, or equivalent practical experience.
- 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.
- Experience with statistical data analysis such as linear models, multivariate analysis, causal inference, or sampling methods.
- Experience with statistical software (e.g., SQL, R, Python, MATLAB, pandas) and database languages along with Statistical Analysis, Modeling and Inference.
- Experience translating analysis results into business recommendations.
- Experience understanding potential outcomes framework and with causal inference methods (e.g., split-testing, instrumental variables, difference-in-difference methods, fixed effects regression, panel data models, regression discontinuity, matching estimators).
- Experience selecting tools to solve data analysis issues.
- Experience articulating business questions and using data to find a solution.
- Knowledge of structural econometric methods.
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About the job
At Google, data drives all of our decision-making. Quantitative Analysts work all across the organization to help shape Google's business and technical strategies by processing, analyzing and interpreting huge data sets. Using analytical excellence and statistical methods, you mine through data to identify opportunities for Google and our clients to operate more efficiently, from enhancing advertising efficacy to network infrastructure optimization to studying user behavior. As an analyst, you do more than just crunch the numbers. You work with Engineers, Product Managers, Sales Associates and Marketing teams to adjust Google's practices according to your findings. Identifying the problem is only half the job; you also figure out the solution.
Responsibilities
- Interact cross-functionally with a variety of leaders and teams, and work with Engineers and Product Managers to identify opportunities for design and to assess improvements for advertising measurement products.
- Collaborate with teams to define questions about advertising effectiveness, incrementality assessment, the impact of privacy, user behavior, brand building, bidding etc., and develop and implement quantitative methods to answer those questions.
- Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct analyses that include data gathering and requirements specification, exploratory data analysis (EDA), model development, and delivery of results to business partners and executives.
- Build and prototype analysis pipelines iteratively to provide insights at scale. Develop knowledge of Google data structures,metrics, advocating for changes where needed for product development.