Senior Staff Research Data Scientist, AI Data

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 a tangible impact on the future of intelligent systems. If you're passionate about data and want to shape the trajectory of AI, your journey starts here.

The US base salary range for this full-time position is $262,000-$365,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Responsibilities

• Work with large, complex 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, 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.