Minimum qualifications:
- Master's degree in Statistics, Economics, Engineering, Mathematics, a related quantitative field, or equivalent practical experience.
- 3 years of experience with statistical data analysis, data mining, and querying (e.g. SQL).
- 1 year of experience managing analytical projects.
- 5 years of experience in applying data analysis to solve business problems in complex, fast-moving, and ambiguous business environments.
- 1 year of experience working in a complex, matrixed organization.
- Experience with statistical software (e.g., R, Python, MATLAB, pandas) and database languages (e.g. SQL).
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About the job
As a Data Scientist at Google, you will be part of a team of Data Scientists in the Consumer Shopping Data Science team. We are looking for a Data Scientist to lead several efforts under multiple workstreams. In this role, you will have the exciting opportunity to shape the future of our AI products at Google Shopping. You will collaborate with a multidisciplinary team of engineers and PMs on a wide range of problems. You'll bring analytical accuracy and statistical methods to the challenges of measuring quality, improving consumer products, and understanding the behavior of our end-users, merchants, and partners. In addition, you will develop, organize, and launch experiments and projects across Engineering, Product Management, Sales, and Marketing.
Responsibilities
- Work with large, complex data sets and solve difficult, non-routine analysis problems. Conduct end-to-end 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 comprehensive understanding of Google data structures and metrics, advocating for changes where needed for both product development and sales activity.
- Interact cross-functionally with a wide variety of leaders and teams, work closely with Engineers and Product Managers to identify opportunities for design, and assess improvements for Google products.
- Make business recommendations (e.g., cost-benefit, forecasting, experiment analysis) with effective presentation 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 facing products.