Description

Minimum qualifications:

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

Preferred qualifications:

• 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.
• Experience developing human evals and autoraters.
• Experience prompting/training large language models and using agentic large language model workflows.

About the jobAs a Senior Research Data Scientist on the Gemini Factuality team, you will be at the center of this mission, ensuring that when users turn to Gemini for information, they receive answers that are both accurate and incredibly helpful.

Our team is responsible for Gemini factuality and quality on information seeking prompts. Our goal is to ensure that our models are as accurate as possible without compromising on any other response quality aspect, and ensuring that response structure and organization are maximally helpful.

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.

Responsibilities

• Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.
• Conduct data analysis on GenAI: evals, performer evals, training data, user logs.
• Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure.
• Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Separately format, re-structure, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.
• Evaluate development, including metrics: human eval templates, autoraters.

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Requisition #: 112940346689626822

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