Data Scientist III, Product - Google Careers

Google · Zürich, Zürich, Switzerland

On-siteWorkplace
3d agoPosted · Sep 4
jobroomSource
$152kdata scientist median
Apply now Opens the original posting at Google. PivotHop does not host applications.
Experience5+ years
EducationBachelor's degree

Skills in this posting

The posting

### Minimum qualifications: ###

* Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.

* 5 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL) (or 2 years work experience with a Master's degree).

### Preferred qualifications: ###

* Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.

* 5 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL).

* 1 year of experience with AI Algorithms.

### About the job ###

Help serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you 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 critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next.

### Responsibilities ###

* Automate data extraction from extensive geospatial datasets to build comprehensive reporting and monitoring dashboards that track business health.

* Conduct large-scale data modeling and analysis to discover strategic improvement opportunities and accurately evaluate initiative impact.

* Design and develop statistical methodologies to evaluate data quality while performing thorough root cause analysis on failure cases.

* Present data-driven findings and insights to key stakeholders in regular syncs, making strategic recommendations to guide product or process enhancements.

* Identify and prioritize high-impact growth opportunities and critical operational challenges, delivering execution and noticeable improvements based on continuous feedback.

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