Senior Staff Data Scientist Manager, AI Data

Senior Staff Data Scientist Manager, AI Data corporate_fare Google place Mountain View, CA, USA bar_chart Advanced Advanced Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain.

Minimum qualifications:

Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field. 10 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of work experience with a PhD degree.

Preferred qualifications:

12 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 10 years of work experience with a PhD degree. 6 years of experience as a people manager within a technical leadership role. About the job Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about . Responsibilities Work with large, data sets. Conduct analysis that includes data gathering and requirements specification, processing, cleaning and curation, analysis, visualization, ongoing deliverables, and presentations. Represent analysis to stakeholders and organization executives in order to insights, influence product direction and answer difficult questions regarding data quality measurement and impact on model performance. Define key metrics that are statistically sound and meaningful to measure data quality for data in various shapes and forms, as well as to measure progress of customer engagement. Research and develop analysis and optimization methods to improve the quality of Google's ML portfolio and applications, including LLM model and training data planning. Conduct independent research and advance the state of understanding in how data impacts ultimate quality of large language models and creating spend optimization priorities with data acquisition.