Senior Staff Research Data Scientist, AI Data Research

Google•Mountain View, CA

3d•$262,000 - $364,000

About The Position

As a Senior Staff Research Data Scientist, you will help advance AI by developing high-quality data that supports advanced Large Language Models. The role calls for deep expertise in machine learning and a strong foundation in core data science methodologies. You will conceive and deploy solutions that contribute directly to AI advancements, work across product and model teams, and help improve Google's models through better training data, data acquisition, and insights. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. The US salary range is $262,000–$364,000 USD, with a 25% bonus target, equity, and benefits.

Requirements

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; alternatively, 8 years of work experience with a PhD degree.

Nice To Haves

12 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases, or statistical analysis; alternatively, 10 years of work experience with a PhD degree.
Experience in Deep Learning, Infrastructure Systems, or Reinforcement Learning.

Responsibilities

Work with data sets and solve complex and ambitious data science problems.
Share and present work to executive stakeholders, defend it effectively, 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 Google's models through better training data, including data acquisition and insights.