- Master's degree in a quantitative discipline (e.g., Statistics, Operations Research, Bioinformatics, Economics, Computational Biology, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering) or equivalent practical experience.
- 2 years of work experience in data analysis related field.
- Experience with statistical software (e.g., R, Python, MATLAB, pandas) and database languages (e.g., SQL)
- PhD degree in a quantitative discipline.
- 4 years of relevant work experience, including expertise with statistical data analysis such as linear models, multivariate analysis, stochastic models, sampling methods.
- Applied experience with machine learning on large datasets.
- Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data.
- Demonstrated leadership and self-direction. Willingness to both teach others and learn new techniques.
- Demonstrated skills in selecting the right statistical tools given a data analysis problem. Effective written and verbal communication skills.
About the job
As a Data Scientist, you will evaluate and improve Google's products. You will collaborate with a multi-disciplinary team of engineers and analysts on a wide range of problems. This position will bring scientific rigor and statistical methods to the challenges of product creation, development and improvement with an appreciation for the behaviors of the end user.
Google is and always will be an engineering company. We hire people with a broad set of technical skills who are ready to take on some of technology's greatest challenges and make an impact on millions, if not billions, of users. At Google, data scientists 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.
- Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. 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 comprehensive knowledge of Google data structures and metrics, advocating for changes where needed for product development.
- Interact cross-functionally, making 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 facing products.