Quantitative UX Researcher: Data-Driven User Insights

Google; Mountain View (CA); On-site; USD 132,000 - 189,000; Full time

Job summary

Google is seeking a Quantitative UX Researcher to join a multidisciplinary team focused on understanding user interactions with ads and search products. You will drive studies, analyze logs and surveys, and apply regression methods to uncover actionable insights that inform product decisions.

Strong background in behavioral research, statistics, and programming is required, with collaboration across engineering and product teams to advance user experiences at scale.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 4 years of experience in product research in an applied research setting, or similar.
• Experience in programming languages used for data manipulation and computational statistics (e.g., Python, R, MATLAB, C++, Java, or Go).
• Experience in experimental design, hypothesis testing, statistical analysis, and survey methodology.

Responsibilities

• Set and drive an original research agenda, drawing on technical expertise in behavioral science, survey science, and data science to advance understanding of user interactions with Google's products.
• Investigate user behavior, UX, and needs using quantitative methods such as logs analysis, surveys, and regression analysis; combine experimental design, statistics, and programming to derive insights.
• Demonstrate rigorous scientific judgment and produce actionable insights in a dynamic environment.
• Collaborate with stakeholders across functions to impact product development at multiple stages.

Skills

Quantitative UX research

Statistical analysis

Experimental design

Survey methodology

Data analysis

Education

Bachelor's degree or equivalent

Master's or PhD in related field

Tools

Python

R

MATLAB

C++

Java

Go

Job description

Google is seeking a Quantitative UX Researcher to join a multidisciplinary team focused on understanding user interactions with ads and search products. You will drive studies, analyze logs and surveys, and apply regression methods to uncover actionable insights that inform product decisions.

Strong background in behavioral research, statistics, and programming is required, with collaboration across engineering and product teams to advance user experiences at scale.