Quantitative UX Researcher, Search

At Google, we follow a simple but vital premise: "Focus on the user and all else will follow." Quantitative User Experience Researchers make this possible.

Google User Experience (UX) is made up of multi-disciplinary teams of UX Designers, Researchers, Writers, Content Strategists, Program Managers, and Engineers who care deeply about the people who use our products. The UX team plays an integral part in gathering insights about the attitudes, emotions, needs, and behaviors of people who use our products to inspire and inform design. We collaborate closely with each other and with engineering and product management to create industry-leading products that deliver value for the people who use them, and for Google’s businesses.

As a Quantitative User Experience Researcher (Quant UXR), you’ll help inform your team of UXers, product managers, and engineers about user needs. You’ll play a critical role in creating useful, usable, and delightful products. You’ll work with stakeholders across functions and levels and have impact at all stages of product development.

You will investigate user behavior and user needs using empirical research methods such as logs analysis, survey research, path modeling, and regression analysis. Quant UXRs vary in background using skills from computer science, quantitative social science, econometrics, data science, survey research, psychology, human-computer interaction, and other fields. You’ll combine skills in behavioral research design, statistical methods, and general programming to improve user experience.

The Quant UXR community at Google will help you do your best work. You’ll have the opportunity to work with and learn from UXRs across Google through regular meetups, mentor programs, and access to internal research tools.

In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $132000 - $190000 (USD) + 15% bonus target + bonus + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Define and measure quantitative UX goals and metrics in collaboration with designers, qualitative researchers, data scientists, engineers, and program managers.
• Develop code and statistical models to understand user experience.
• Conduct empirical research using methods from computer science, quantitative social science, statistics, econometrics, and other fields to understand user behavior and extract meaningful patterns from large data sets.
• Examine existing data and product designs to generate hypotheses and plans for high-impact research.
• Prioritize and drive research to improve user experience. Communicate findings to stakeholders in the company and make research findings convincing and actionable for both research experts and non-experts.

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 4 years of experience 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 survey design and statistics.

Preferred qualifications:

• Master's or PhD degree in Human-Computer Interaction, Cognitive Science, Statistics, Psychology, Anthropology, or related field.
• 3 years of experience working with executive leadership (e.g., director-level and above).
• 2 years of experience conducting UX research on products, managing projects, and working in a large, matrixed organization.
• Experience in programming computational and statistical algorithms for large data sets.
• Knowledge of research questions within a given domain and technical tools for the analysis of data within that field.
• Knowledge of descriptive, inferential, and multivariate statistics, including t-test and ANOVA, and experimental design.

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: New York, NY, USA; Mountain View, CA, USA.