The role
From Google's own posting.
At Google, data drives all of our decision-making. In the Data Scientist - Research role, you will 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 will 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. You will 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.
Google is and always will be an engineering company. We hire people with a broad set of technical skills who are ready to address some of technology's greatest challenges and make an impact on millions, if not billions, of users. At Google, engineers not only revolutionize search, they routinely work on massive scalability and storage solutions, large-scale applications and entirely new platforms for developers around the world. From Google Ads to Chrome, Android to YouTube, Social to Local, Google engineers are changing the world one technological achievement after another.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $118000 - $157000 (USD) + 0% bonus target
Learn more about benefits at Google .
Work with large complex data sets, solve difficult non-routine analysis problems, and apply advanced analytical 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.
Interact cross-functionally with a wide variety of people and teams. Work closely with engineers to identify opportunities, design and assess improvements to Google products.
Make business recommendations (e.g., cost-benefit, forecasting, experiment analysis) 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 products.
Minimum qualifications:
Currently pursuing a PhD degree in a quantitative discipline (e.g., statistics, biostatistics, physics, applied mathematics, operations research, economics).
Experience with statistical methods (linear models, multivariate analysis, stochastic processes, sampling methods, etc.).
Experience with data analysis.
Experience using R or Python and technology to work with datasets such as scripting or statistical software (R, SAS, etc.).
Preferred qualifications:
Currently attending a degree program in the US and available to work full time for 12 weeks outside of university term time.
In their penultimate academic year or returning to a degree program after completion of the internship.
Ability to draw conclusions from data and recommend actions.
Ability to take on a leadership role and take initiative.
Interest in learning new techniques.
Currently pursuing a PhD degree in a quantitative discipline (e.g., statistics, biostatistics, physics, applied mathematics, operations research, economics).
Experience with statistical methods (linear models, multivariate analysis, stochastic processes, sampling methods, etc.).
Experience with data analysis.
Experience using R or Python and technology to work with datasets such as scripting or statistical software (R, SAS, etc.).