The role
From Google's own posting.
In the Data Scientist product role, you will provide quantitative analysis, market expertise and a strategic perspective to our partners throughout the organization. As a member of the team, you'll serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make key recommendations for Googlers in Engineering and Product Management.
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: $94000 - $125000 (USD) + 0% bonus target
Learn more about benefits at Google .
Conduct data analysis to make business or product recommendations (i.e., cost-benefit, invest-divest, forecasting, impact analysis).
Deliver effective presentations of findings and recommendations to multiple levels of stakeholders, creating visual displays of quantitative information.
Collaborate with cross-functional stakeholders to understand their business needs, formulate and complete analysis that includes data gathering, analysis, ongoing scaled deliverables and presentations.
Help Google to focus on key decisions to improve products and services.
Minimum qualifications:
Currently pursuing a Master's degree in a quantitative field (e.g., Statistics, Computer Science, Engineering, Mathematics, Data Sciences, etc.).
Experience working with statistical packages (e.g., R, SAS, Stata, MATLAB, etc.).
Experience articulating product questions, pulling data from datasets (SQL), and using statistics to arrive at an answer.
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.
Experience articulating product questions, pulling data from datasets (SQL or Python), and using statistics to arrive at an answer.
Ability to translate analysis results into business recommendations.
Interest and ability to work with data, metrics, analysis and trends and applied knowledge of measurement, statistics and program evaluation.
Excellent problem-solving, written/verbal communication, and business judgment skills.
Currently pursuing a Master's degree in a quantitative field (e.g., Statistics, Computer Science, Engineering, Mathematics, Data Sciences, etc.).
Experience working with statistical packages (e.g., R, SAS, Stata, MATLAB, etc.).
Experience articulating product questions, pulling data from datasets (SQL), and using statistics to arrive at an answer.