Google

Runs Search and YouTube and builds Gemini AI

Data Scientist - Product, Search AI Experiences

Data ScienceUpdated on Nov 10

Full-timeMountain View, CA, USAIn-person

About the Job

Requirements

A Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field is required.
Five years of experience with analysis applications, such as extracting insights, performing statistical analysis, or solving business problems, and coding in Python, R, or SQL; alternatively, two years of that experience with a Master's degree.
A Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field is preferred.
Five years of experience with analysis applications, such as extracting insights, performing statistical analysis, or solving business problems, and coding in Python, R, or SQL, is preferred.

Responsibilities

Frame and solve ambiguous product problems and communicate results clearly to technical and non-technical audiences.
Work cross-functionally with Product, Engineering, UX, and Research partners, acting as a thought partner and influencing prioritization with data.
Define success metrics and quality frameworks for multi-step and conversational AI experiences in Search, spanning task completion, efficiency, trust, and user satisfaction.
Analyze human and auto-rater evaluations of AI experiences alongside behavioral signals to build a holistic view of product quality.
Design and assess live experiments to understand the impact of new AI features on user journeys, and make clear launch recommendations.
Develop new metrics and evaluation approaches, design experiments for complex user flows, and translate findings into product direction using techniques such as LLM-based evaluation and causal inference.

Frame and solve ambiguous product problems and communicate the results clearly to both technical and non-technical audiences.
Work cross-functionally with Product, Engineering, UX, and Research partners. Act as a thought partner and influence prioritization with data.
Define success metrics and quality frameworks for multi-step and conversational AI experiences in Search, spanning task completion, efficiency, trust, and user satisfaction.
Analyze human and auto-rater evaluations of AI experiences alongside behavioral signals to build a holistic view of product quality.
Design and assess live experiments to understand the impact of new AI features on user journeys, and make clear launch recommendations.

Minimum qualifications:

Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
5 years of experience with analysis applications (e.g., extracting insights, performing statistical analysis, or solving business problems), and coding (e.g., Python, R, SQL) or 2 years of experience with a Master's degree.

Preferred qualifications:

Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
5 years of experience with analysis applications (e.g., extracting insights, performing statistical analysis, or solving business problems), and coding (e.g., Python, R, SQL).

In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on.

In this role, you will work cross-functionally with leads from Engineering, Product, UX, and Research to shape how AI-powered experiences in Search are measured and improved. As AI systems across the industry become more capable at reasoning through complex, multi-step goals, the question of what "success" means for a search journey is evolving, and you will help define that answer: by developing new metrics and evaluation approaches, designing experiments for complex user flows, and translating findings into product direction. Your work will directly inform the future of Google Search and AI Mode, applying techniques like LLM-based evaluation and causal inference to some of the most consequential product questions at Google.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $138000 - $197000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
5 years of experience with analysis applications (e.g., extracting insights, performing statistical analysis, or solving business problems), and coding (e.g., Python, R, SQL) or 2 years of experience with a Master's degree.

About the Company

Google

Runs Search and YouTube and builds Gemini AI

Google runs the world's most used search engine and free services such as YouTube, Android, and Gmail, and it builds the Gemini AI models that work inside them. In 2017, its researchers invented the transformer, the neural network design behind ChatGPT and most other AI chatbots. People use these services without paying, and Google earns most of its money from ads placed beside search results and YouTube videos. Businesses rent computing power and Gemini models through Google Cloud, and Google also sells subscriptions and Pixel phones. Larry Page and Sergey Brin founded Google in 1998 as Stanford PhD students; it is based in Mountain View, California, United States, and is the main business of parent company Alphabet.

Company size: 10,001+
Company stage: IPO
Headquarters: Mountain View, CA
Founded: 1998

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