Data Scientist, Research, Search Platform - Google
Cambridge, MA
About the Job
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Cambridge, MA, USA; Mountain View, CA, USA.Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
Minimum qualifications:
- Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
- 8 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.
Preferred qualifications:
- 6 years of experience (e.g., statistician/bioinformatician/product analyst), including with statistical data analysis such as linear models, multivariate analysis, causal inference, sampling methods engagements outside class work at school can be included.
- Experience translating analysis results into business recommendations.
- Experience in articulating business questions and using mathematical techniques to find an answer using available data.
- Ability to select the appropriate statistical tools for a given data analysis problem, along with demonstrated effectiveness in both written and verbal communication skills.
- Ability to lead and take initiative, along with a demonstrated willingness to teach others and learn new techniques.
About the job
In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.The US base salary range for this full-time position is $177,000-$266,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Work with data sets. Solve difficult, non-routine analysis problems, applying advanced problem-solving methods as needed. Conduct analysis including data gathering and requirements specification, processing, analysis, 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 products development and business activity.
- Interact cross-functionally with many people and teams. Work with engineers to identify opportunities for, design, and assess improvements to google products.
- Make business recommendations (e.g. cost-benefit, forecasting, experiment analysis) with presentations of findings at multi-level stakeholders through visual displays of quantitative information.
- Research and develop analysis, forecasting methods to improve the quality of Google's user facing products; examples include ads quality, search quality, end-user behavioral modeling, and live experiments.
Source : Google