Google is looking for a data scientist to help serve its worldwide user base by providing quantitative support, market understanding, and strategic perspective to partners, using data to drive decision-making, make recommendations, measure ROI, and identify new opportunities for AI products and infrastructure.
Requirements
- 10 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 8 years work experience and a Master's degree).
- 12 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
Responsibilities
- Perform analysis utilizing relevant tools (e.g., SQL, R, Python).
- Provide analytical thought leadership through proactive and strategic contributions (e.g., suggests new analyses, infrastructure or experiments to drive improvements in the business).
- Own outcomes for projects by covering problem definition, metrics development, data extraction and manipulation, visualization, creation, implementation of analytical/statistical models, and presentation to stakeholders.
- Develop solutions, lead, and manage problems that may be ambiguous and lacking clear precedent by framing problems, generating hypotheses, and making recommendations from a perspective that combines both, analytical and product-specific expertise.
- Oversee the integration of cross-functional and cross-organizational project/process timelines, develop process improvements and recommendations, and help define operational goals and objectives.
- Directly or indirectly oversee the contributions of others and develop colleagues’ capabilities in the area of specialization.
Other
- Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
- Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
- Weave stories with meaningful insight from data.
- Make critical recommendations for your fellow Googlers in Engineering and Product Management.
- Relish tallying up the numbers one minute and communicating your findings to a team leader the next.
