Senior Quantitative UX Researcher – Search Verticals Growth
| Company | |
|---|---|
| Location | San Francisco, CA, USA, New York, NY, USA, Mountain View, CA, USA |
| Salary | $151000 – $222000 |
| Type | Full-Time |
| Degrees | Bachelor’s |
| Experience Level | Senior |
Requirements
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience in an applied research setting, or similar.
- 4 years of experience conducting mixed methods research, designing and analyzing surveys and data in an industry or academic environment.
- Experience in programming languages used for data analysis and computational statistics (e.g., Python, R, MATLAB, C++, Java, or Go).
- Experience with research design utilizing various methods (e.g., usability studies, contextual inquiry, surveys, etc.).
Responsibilities
- Define and measure quantitative UX goals and metrics in collaboration with Designers, Qualitative Researchers, Data Scientists, Engineers and Program Managers.
- Conduct empirical research using methods from computer science, quantitative social science, statistics, econometrics, and other fields to understand user behavior and extract patterns from data sets.
- Examine existing data and product designs to generate hypotheses and plans for research.
- Prioritize and deliver research to improve user experience. Communicate findings to stakeholders in the company. support with research findings for both research experts and non-experts.
- Craft quantitative surveys to user behaviors and needs and develop code or statistical models to understand user experience.
Preferred Qualifications
- Master’s degree or PhD in Computer Science, Human-Computer Interaction, Statistics, Psychology or a related field, or equivalent practical experience.
- 5 years of experience conducting UX research on products and working with executive leadership (e.g., Director level).
- 3 years of experience managing projects, and working in an organization.
- Experience in descriptive, inferential, and multivariate statistics, including t-test and ANOVA, and experimental design.
- Experience in programming computational and statistical algorithms for data sets.
- Excellent collaboration and communication skills, across peers and executive management, building consensus and driving technical decisions with various sized customer stakeholder groups.