Quantitative User Experience Researcher, Early Career

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; Atlanta, GA, USA; Austin, TX, USA; Los Angeles, CA, USA; New York, NY, USA; Seattle, WA, USA; San Francisco, CA, USA; Sunnyvale, CA, USA.

Qualifications

Minimum qualifications:

Bachelor’s degree in Human Computer Interaction, Computer Science, Information Science, Statistics, or related field, or equivalent practical experience.

1 year of experience with quantitative research design utilizing various methods including: descriptive statistics, multivariate data visualization, multivariate regression, bootstrap methods, logs analytics, and text analytics.

Experience in Stata, C++, R, or Python.

Preferred qualifications:

Master's degree in Human Computer Interaction, Computer Science, Information Science, Statistics, or related field, or equivalent practical experience.

Relevant research experience with User Experience or Human-Computer Interaction teams.

Experience demonstrating excellent command of research questions within a given domain, and of technical tools for the analysis of data within that field.

Working knowledge of statistics, multivariate statistics, and experimental design.

Proficiency in programming computational and statistical algorithms for large data sets.

Ability to communicate complex concepts clearly and persuasively across different audiences and varying levels of the organization.

About the job

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.

Responsibilities

Define and measure quantitative UX goals and metrics in collaboration with Designers, Qualitative Researchers, Engineers, and Product Managers.

Examine existing data and product designs to generate hypotheses and plans for high-impact research.

Prioritize and drive research to improve user experience.

Develop code and statistical models to understand user experience.

Drive change by communicating findings to stakeholders in the company. Make research findings convincing and actionable for both research experts and non-experts.