Data Scientist III, Product - Google Careers
Google · Zürich, Zürich, Switzerland
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.
The PivotHop read
- What a data scientist actually earnsmedian, seniority, by country
- What data scientists do insteadevery measured route out
- Machine Learning Engineer → Data Scientist70% readiness
- All open data scientist rolesthe full board
Where these skills also reach
- 530 open data analyst roles60% readiness from data scientist
- 82 open product analyst roles56% readiness from data scientist
- 578 open research scientist roles55% readiness from data scientist
- 294 open machine learning engineer roles53% readiness from data scientist
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