Staff UX Quant Researcher — AI Ad Sales (Equity)

Google LLC; Mountain View (CA); On-site; USD 188,000 - 274,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

Google LLC in Mountain View, CA is seeking a Staff UX Quantitative Researcher for Agentic AI Ad Sales. You will join a multi-disciplinary UX team to uncover user needs, design primary research, and influence product development at scale.

You will apply statistical methods to understand behaviors, collaborate with PMs/engineers/designers, and translate findings into shipped product impact, including impact on revenue and seller effectiveness.

Qualifications

• Bachelor's degree in Human-Computer Interaction, Cognitive Science, Statistics, Psychology, Anthropology, or related field.
• 8 years of experience in an applied research setting.
• Experience with data manipulation and computational statistics languages (Python, R, MATLAB, Java, or Go).
• Experience with evaluating agentic AI and multi-agent architectures.

Responsibilities

• Apply statistical methods to analyze large-scale log data, survey data, and behavioral data.
• Partner with product managers, engineers, and designers to identify research opportunities and define success metrics.
• Translate complex findings into actionable insights for cross-functional stakeholders.
• Collaborate with qualitative UXRs, data scientists, and analysts to triangulate findings.
• Design and analyze evaluation systems for agent routing quality and bias mitigation.

Skills

Statistical methods

Experimental design

Data analysis

Cross-functional collaboration

Python

R

MATLAB

Java

Go

Education

Bachelor's degree in HCI/CS/Stats/Psychology

Tools

Python

R

MATLAB

Java

Go

Job description

Google LLC in Mountain View, CA is seeking a Staff UX Quantitative Researcher for Agentic AI Ad Sales. You will join a multi-disciplinary UX team to uncover user needs, design primary research, and influence product development at scale.

You will apply statistical methods to understand behaviors, collaborate with PMs/engineers/designers, and translate findings into shipped product impact, including impact on revenue and seller effectiveness.