Data Scientist, Product, Google Home
Job Summary
Job Description
- Bachelor's degree in quantitative field
- 5 years of experience with analysis and coding (or 2 years with advanced degree)
- Proficient in SQL, R, Python
- Strong analytical and communication skills
- Experience with Machine Learning models
- Master's degree in quantitative field
4 skills required
Job Details
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 (e.g., extracting insights, performing statistical analysis, or solving business problems), and coding (e.g., Python, R, SQL) or 2 years of work experience with an advanced degree.
Preferred qualifications:
- Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
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.
We are the Devices Insights and Analytics team and are part of the Platform and Devices Product Area. Our mission is to be a true insights and analytical source of competitive advantage to our product area. We inspire and deliver transformational action for our products and business with the customer at the center. We drive customer centricity by aligning business and customer needs.
Responsibilities
- Arrange high-level business questions into data-focused investigative hypothesis. Write queries and perform analysis to answer business questions (e.g., SQL, R, Python).
- Develop and automate reports, iteratively build dashboards to provide insights at scale, solving for business priorities.
- Apply Large Language and other Machine Learning models to analyze structured and unstructured data (e.g., for Natural Language Processing).
- Generate insights from user sentiment and behavior to recommend product improvements and strategy.Protect team against overreaching statistical conclusions (e.g., sampling, correlation/causation).
- Deliver effective presentations of findings and recommendations to multiple levels of stakeholders, creating visual displays of quantitative information.Manage stakeholders, solicit ideas, prioritize, and manage expectations.
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