Senior UX Quantitative Researcher, Agentic AI
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Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 6 years of experience in product research in an applied research setting.
- Experience in programming languages used for data manipulation and computational statistics (e.g., Python, R, MATLAB, C++, Java, or Go).
- Experience applying statistical methods (e.g., significance testing, regression, experimental design) to behavioral data.
- Experience designing and executing human evaluation frameworks (crowdsourced raters, domain experts) and auditing or validating automated rating systems.
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.
- 3 years of experience managing projects, and working in a large, matrixed organization.
- Experience analyzing user behavior in B2B contexts, enterprise software, CRM platforms, or support tooling, and evaluating multi-agent architectures or workflows, built on Experience analyzing user behavior in B2B contexts, enterprise software, CRM platforms, or support tooling.
- Direct experience evaluating multi-agent architectures, agentic workflows, orchestrators, or complex subagent routing systems.
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.Deliver AI-powered sales insights and experiences to enable sellers to do more and win bigger. Enable advertisers to grow successfully.
Connect Sales is the primary Customer Relationship Management (CRM) powering Google Ads Sales, managing 99% of Google’s Ads revenue. As we transform the platform with agentic AI, we are building intelligent workflows that route, synthesize, and resolve complex seller and advertiser tasks across general and specialized agents.
As a Quantitative UX Researcher in Customer Engagement, you will apply rigorous quantitative methods to understand the end-to-end experience of users interacting with our sales and marketing platforms. You will analyze behavioral data (e.g., product logs, surveys) to identify user pain points, measure user satisfaction and efficiency, evaluate AI outputs and provide data-driven recommendations that shape product strategy and improve the user experience. You will partner with designers, product managers, engineers, and other researchers to deliver actionable insights that make our tools more effective for our users.
Our work directly impacts billions of users by protecting users from harm, improving ad quality, and optimizing campaigns for advertiser return-on-investment. We foster a culture of deep collaboration, partnering closely with teams like Google Research and DeepMind to solve complex challenges. Join us to work on state-of-the-art AI, take on problems at an unparalleled scale, and build the next generation of advertising technology.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
- Define, plan, and conduct quantitative research to evaluate user behavior on platforms, and Independently define, plan, and conduct quantitative research to evaluate user behavior on CE platforms.
- Apply statistical methods (e.g., statistical inference, regression modeling, experimental design) to analyze large-scale log data, survey data, and other behavioral data.
- Partner with product managers, engineers, and designers to identify research opportunities, define user-centered success metrics, and ensure appropriate data instrumentation.
- Evaluate, analyze, and interpret A/B experiments to measure the impact of product changes on user behavior and key metrics.
- Develop and analyze human and synthetic evaluation systems, applying crossed rater/item statistical models and Bradley-Terry preference frameworks to calibrate agent routing quality.
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