Senior Research Data Scientist, AI Data

Minimum qualifications:

• Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
  
• 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of work experience with a PhD degree.
  

Preferred qualifications:

• 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.
  

About the job

Imagine placing yourself at the very epicenter of the AI revolution, where your unique expertise directly fuels the next generation of Large Language Models. The Data Intelligence team in the AI Data organization aims at becoming the critical driving channel behind the high-quality human expert data that trains, assesses, and elevates the Gemini family of models. This data isn't just information—it is the essential ingredient required for unlocking unprecedented AI breakthroughs and ensuring these models are safe, helpful, and exceptionally capable. By joining us, you will partner with some of the great minds in the industry to define the global standard for data excellence. You will move beyond theory to make a tangible, lasting impact on the future of intelligent systems used by millions around the world. If you are deeply passionate about the power of data and driven to shape the trajectory of artificial intelligence, your journey starts right here.

The US base salary range for this full-time position is $174,000-$252,000 + 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.
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 benefits at Google.
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 benefits at Google.

Responsibilities

• Focus on post training data for Large Language Models (LLMs), loss pattern analysis, data quality and impact.
• Handle challenging data science problems related to AI models evaluation and training. Utilize AI models and tools as integral components for evaluating, synthesizing, and understanding complex datasets.
• Contributes to the design and implementation of novel data acquisition and quality improvement techniques for foundational models.
• Contributes to new methodologies to improve the performance of Google's models through better training data, including data acquisition, and insights.
• Works cross-functionally with Research, Engineering, and Product teams (e.g., Cloud AI Data and DeepMind).