Senior Data Scientist, AI Data

Key Skills

Aartificial intelligence, Data science techniques, Python Programming, R Programming, SQL

Job Description

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

Google is an AI first company and is leading the efforts in principled AI adoption. We deeply care about the quality of the machine learning data and models used in production. Towards this goal, we are directly supporting the Gemini team and other Product Areas. Our mission is to improve the quality of models that Google releases through its various product offerings by providing tools and services for making faster and easier to reach model quality goals.

AI in the Gemini Era is profoundly data-centric: the “quality” of the data used for training, fine-tuning, or RAG, matters more to the performance of the end product than almost anything else. Where it becomes interesting is when we ask ourselves what “quality” means exactly and also what is the value of some specific data. It is very complex, model and use-case dependent, and the techniques that approximate it the best are often found on the frontiers of research.

Our mission is to dramatically improve the time to model quality for our users. We do so by bringing Data Optimization techniques to a broad audience through integrated tools and platforms. We build and iterate on tools to automatically and efficiently apply state of the art data optimization techniques. We demonstrate to our users which ones work best for their use case, and deliver insights on how to improve further. We’re working with key product teams across Google.

The US base salary range for this full-time position is $150,000-$223,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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 large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct end-to-end 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 measurement and impact on model performance.
• Build and prototype analysis pipelines iteratively to provide insights at scale. Work closely with product teams to incorporate important analysis into existing framework and tools.
• Interact cross-functionally with a wide variety of product and model teams. Work closely with engineers to identify opportunities for, design, and assess improvements of data quality and model performance.