Staff Mixed-Methods UX Researcher - AI Enablement

• Design and execute end-to-end mixed-methods studies combining qualitative methods (in-depth interviews, workflow observations, usability studies, concept evaluations) with quantitative methods (surveys, telemetry, large-scale behavioral logs).
• Define, instrument, and track user-centered
  key performance indicators and product health indicators, triangulating qualitative workflow pain points with quantitative impact attribution across AI data pipelines.
• Build and use agent-assisted pipelines, synthesis workflows, and analysis scripts to pair unstructured qualitative feedback with operational and telemetry logs.
• Investigate developer and data-practitioner mental models alongside system performance signals to diagnose and reduce user friction, efficiency losses, and cognitive load.
• Partner with Product Managers, Engineers, UX Designers, Data Scientists, and ML researchers to translate mixed-methods evidence into product direction.

Minimum qualifications:

• Bachelor's degree in Human-Computer Interaction, Cognitive Science, Psychology, Information Science, Statistics, Computer Science, a related field, or equivalent practical experience.
• 8 years of experience conducting user research in an applied product or technology setting or 6 years with an advanced degree.
• Experience leading mixed-methods research combining qualitative methods (interviews, usability testing, field studies) with quantitative methods (survey design, behavioral logs analysis, metrics definition).
• Experience analyzing quantitative and behavioral data using statistical or scripting tools such as Python, R, or SQL.

Preferred qualifications:

• Master's degree or PhD in Human-Computer Interaction, Cognitive Psychology, Information Science, Statistics, Computer Science, or a related field.
• Experience researching complex technical domains such as AI/ML products, data systems, developer APIs, or technical infrastructure.
• Experience defining and tracking user-centered
  Key Performance Indicators (KPIs) and Product Health indicators aligned with Critical User Journeys.
• Experience partnering with cross-functional engineering, data science, and product leadership to translate mixed-methods insights into product and platform strategy.

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.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: $188000 - $274000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sunnyvale, CA, USA; Seattle, WA, USA.

• Bachelor's degree in Human-Computer Interaction, Cognitive Science, Psychology, Information Science, Statistics, Computer Science, a related field, or equivalent practical experience.
• 8 years of experience conducting user research in an applied product or technology setting or 6 years with an advanced degree.
• Experience leading mixed-methods research combining qualitative methods (interviews, usability testing, field studies) with quantitative methods (survey design, behavioral logs analysis, metrics definition).
• Experience analyzing quantitative and behavioral data using statistical or scripting tools such as Python, R, or SQL.