Walmart Staff Design Researcher - Quantitative Research 

United States, California, Sunnyvale 

58510488

. .

As a Quantitative User Experience Researcher (Quant UXR), , product managers, and engineers about user needs. play a critical role in creating useful, usable, and delightful products. work with stakeholders across functions and levels and have 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.

Responsibilities

• Engineers and Program Managers.

• Examine existing data and product designs to answer questions around user experiences and generate hypotheses and plans for high-impact research.

• 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.

• Prioritize and drive research to improve user experience.

• Communicate findings to stakeholders , ensuering research findings are robust, convincing and actionable for research, UX, and product teams .

• Lead, oversee and contribute to experimental design testing.

Minimum qualifications:

• Bachelor's degree in Human -Computer Interaction, Cognitive Science, Statistics, Psychology, Anthropology, related field, or equivalent practical experience.

• 4+ years of experience in an applied research setting, or similar.

• Product research experience in an applied research setting, preferably in a large, matrixed organization.

• Experience in programming languages used for data manipulation and computational statistics (Python, R, MATLAB, C++, Java, Go), and with SQL.

Preferred qualifications:

• Master's degree or PhD in Human-Computer Interaction, Cognitive Science, Statistics, Psychology, Anthropology, or related field.

• 5 years of experience conducting UX research on products and working with executive leadership (e.g., Director level and above).

• Excellent command of research questions within a given domain, and of technical tools for the analysis of data within that field.

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

• Demonstrated expertise in descriptive, inferential, and multivariate statistics, including t-test and ANOVA, and experimental design.