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, or equivalent experience in machine learning, statistics, or related field.
- Experience with the full Machine Learning product lifecycle, from ideation to exploration, productionization, and support.
- Experience applying Machine Learning and advanced analytics solutions to enterprise operations teams.
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.
- Provide leadership through proactive and contributions; consistently use insights and analytics to drive decisions and alignment throughout the organization.
- Work in a team covering problem definition, metrics development, data extraction and manipulation, visualization, creation, implementation of problem-solving/statistical models, and presenting to stakeholders.
- Define and report Key Performance Indicators (KPIs) and launch impact as part of regular business reviews with the cross-functional and cross-organizational leadership team.
- Design and develop machine learning models to solve problems within the Enterprise Support space that solve business problems for Google. Work alongside Machine Learning Engineering teams to test and deploy generative AI models to internal Googler customers.
- Review analysis and business cases conducted by others to provide feedback.
