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About the Role
As a Business Data Scientist, you will translate business problems into analytical solutions and insights, provide technical mentorship, implement data science solutions, improve data pipelines, develop evaluation metrics, and build statistical models. You will create and implement reused and scaled solutions, collaborate with supported teams, and translate business needs into tractable analyses or evaluation metrics. You will work closely with product and engineering teams to analyze impact on product or Google-wide metrics.
Responsibilities
- 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, making business recommendations with effective presentations of findings at multiple levels of stakeholders through visual displays of quantitative information.
- Develop and automate reports, and iteratively build and prototype dashboards to provide insights at scale, solving for business priorities.
- Design and analyze controlled experiments or counterfactual causal inference studies to examine the incremental impact of business, product, or go-to-market initiatives.
Requirements
- Currently pursuing a PhD degree in a quantitative discipline (e.g., statistics, biostatistics, physics, applied mathematics, operations research, economics).
- Experience with statistical methods (i.e., linear models, multivariate analysis, stochastic processes, sampling methods, etc.).
- Experience with statistical software (e.g., R, Python, MATLAB) and database languages (i.e., SQL).
- 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 leveraging data insights into storytelling for business stakeholders.
- Experience in controlled experiment design and causal inference methods.
- Ability to prioritize requests and partner well in an environment with competing demands from stakeholders.
Skills
- Statistical methods
- Linear models
- Multivariate analysis
- Stochastic processes
- Sampling methods
- R
- Python
- MATLAB
- SQL
- Data insights
- Storytelling
- Controlled experiment design
- Causal inference methods
- Prioritization
- Stakeholder management
Location
- US
Work Type
- Full-time
Experience Level
- PhD student
- Penultimate academic year
Education Level
- PhD
Salary/Compensations
- $118000 - $157000 (USD)
Benefits
- 0% bonus target
- Learn more about benefits at Google [https://www.google.com/about/careers/applications/benefits/].
About the Company
- 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.
Equal Opportunity
- Individual pay is determined by factors including job-related skills, experience, and relevant education or training.