Imagine being at the core of the AI revolution, where your expertise directly fuels the most advanced Large Language Models. We are the driving team behind high-quality data – the essential ingredient for unlocking unprecedented AI breakthroughs. Partner with resourceful minds, define data excellence, and make an impact on the future of intelligent systems. As a Senior Staff Research Data Scientist, you will be a key driver of innovation. This role demands deep expertise in machine learning and a strong foundation in core data science methodologies. You'll be instrumental in conceiving and deploying solutions, directly contributing to the advancements of AI. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $262000 - $364000 (USD) + 25% bonus target + equity + benefits Learn more about benefits at Google. Responsibilities • Work with data sets and solve complex and ambitious data science problems. • Share/present to executive stakeholders and executives, effectively defend your work, and influence strategy and product direction. • Interact cross-functionally with a wide range of product and model teams. Work closely with Product Management and engineering to identify opportunities. • Define key metrics to measure success in various shapes and forms. • Develop new methodologies to improve the performance of Google's models through better training data, including data acquisition, and insights. Minimum qualifications: • Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, a related quantitative field, or equivalent practical experience. • 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. • Experience in Deep Learning, Infrastructure Systems, or Reinforcement Learning.