Senior Staff Data Scientist Manager, AI Data

Minimum qualifications:

• Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
  
• 8 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of experience with a PhD degree.

Preferred qualifications:

• 10 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of experience with a PhD degree.
• 3 years of experience as a people manager within a technical leadership role.
  
• Experience with modern machine learning techniques, including sequence/transformer modeling experience in NLP/speech domains.

About the job

As a part of Machine Learning (ML), Systems and Cloud AI (MSCA), we believe that quality data is key to building better ML models, especially in the era of Large Language Models (LLMs). We work directly with model teams to define, measure, and improve data quality, promote best practices, and increase data availability and awareness.

The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

The US base salary range for this full-time position is $197,000-$291,000 + 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.

Responsibilities

• Work with data sets and solve difficult, non-routine analysis problems, applying advanced problem-solving methods as needed. Conduct analysis that includes data gathering and requirements specification, processing, cleaning and curation, analysis, visualization, ongoing deliverables, and presentations.
• Share/present analysis to relevant stakeholders and organization executives in order to share insights, influence product direction and answer difficult questions regarding data quality and impact on model performance.
• Interact cross-functionally with a wide variety of product and model teams.
• Define data quality for data in various shapes and forms.
• Research and develop analysis and optimization methods to improve the quality of Google's Machine Learning (ML) portfolio and applications, including Large Language Model (LLM) model and training data planning.