Senior Quantitative UX Researcher, AI Enablement

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.

• 6 years of experience in product research in an applied research setting.

• Experience in quantitative research, logs analysis, measurement and attribution, data analysis, and metrics analysis.

• Experience researching AI/ML products, Developer APIs, or technical infrastructure.

• Experience in programming languages used for data manipulation and computational statistics (e.g., Python is the preference).

Preferred qualifications:

• Master's degree or PhD in Human-Computer Interaction, Cognitive Science, Statistics, Psychology, Anthropology, or related field.

• 5 years of experience conducting UX research on products and working with executive leadership (e.g., Director level and above).

• Experience with code reviews.

• Experience analyzing behavioral telemetry/log data (e.g., AI logs or SQL) to inform product decisions.

• Experience working with agentic AI tools, Loop Engineering principals, and AI/ML training phases and methods.

About the job:

At Google, we "Focus on the user and all else will follow." As a Quantitative User Experience Researcher (Quant UXR), you make this possible. You will join a multi-disciplinary team, collaborating closely with Engineering and Product Management to create industry-leading, innovative products.

You will drive impact at all stages of development by investigating user behavior through empirical methods like log analysis, survey research, and regression. We value various educational experiences—from Computer Science to Psychology—and require a blend of behavioral research design, statistical proficiency, and programming skills to uncover actionable insights. Beyond the work, you will grow within a supportive Quant UXR community offering mentorship, regular meetups, and exclusive internal tools to help you thrive.

As a Senior Quantitative UX Researcher, you will drive product excellence for Alphabet’s core AI infrastructure by translating complex system telemetry into actionable user insights. As a part of the AI Enablement side of the ACE UX research team, you will execute on partnerships with AI Data and Research-to-Production (R2P). You will lead the development of next-generation measurement frameworks, leveraging advanced statistical models and agentic AI workflows to analyze system logs at scale. You will partner closely with Engineering, Product Management, and agentic developers, pioneer how we measure and optimize frictionless, high-velocity developer workflows across the AI pipeline.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $159000 - $230000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google. Responsibilities:

• Design and implement agent-assisted pipelines to parse, audit, and analyze massive-scale system logs (e.g., telemetry, clickstream, operational logs) to accelerate insight generation.

• Define, instrument, and track system-level Key Performance Indicator (KPIs), backend performance metrics, and Product Health indicators, aligning them directly with Critical User Journeys.

• Develop custom scripts, prompts, or agentic wrappers (e.g., in Python or R) to parse complex, messy infrastructure logs and transform them into digestible, statistically validated behavioral patterns.

• Lead the design and analysis of complex experiments, multivariate testing, and rollout strategies to optimize system configurations, documentation, and tooling.

• Collaborate with Infrastructure Engineers, Applied Data Scientists, and Machine Learning researchers to ensure backend pipelines are correctly instrumented for downstream agentic analysis.