Quantitative UX Researcher (Temporary)

📍 Job Overview

Job Title: Quantitative UX Researcher (Temporary)

Company: User Research International

Location: United States (Remote)

Job Type: TEMPORARY

Category: User Experience Research / Data Analytics

Date Posted: 2026-04-24

Experience Level: 5+ Years

Remote Status: Remote Solely

🚀 Role Summary

• Lead end-to-end survey design, programming, and deployment for quantitative user research projects, ensuring robust sampling strategies and data quality.

• Conduct sophisticated statistical analyses using industry-standard tools such as R, SPSS, or SAS to uncover key user insights and trends.

• Translate complex quantitative findings into clear, compelling narratives and actionable recommendations for product, engineering, and design teams, particularly within AI-focused domains.

• Develop and track key user experience metrics to inform product strategy and measure the impact of design decisions.

📝 Enhancement Note: While the role is listed as "Quantitative UX Researcher," its responsibilities heavily lean into data analytics, statistical modeling, and research operations. Candidates should highlight experience in process optimization, data quality assurance, and efficient research execution. The "AI-focused domains" mention suggests a need for adaptability and potential familiarity with emerging technologies.

📈 Primary Responsibilities

• Design, program, and launch user research surveys, managing sampling strategies, deployment, and rigorous data quality checks to ensure reliable insights.

• Perform descriptive and advanced statistical analyses using R, SPSS, SAS, or similar statistical software to identify patterns and trends in user behavior data.

• Apply various survey and measurement techniques, including tree testing, card sorting, MaxDiff, and conjoint analysis, to gather specific user preference and usability data.

• Conduct thematic or pattern-based analysis on existing datasets (e.g., bug reports, customer feedback) to identify emerging issues and long-term trends.

• Create impactful data visualizations and communicate research findings through presentations, interactive dashboards, and detailed written reports to diverse stakeholders.

• Collaborate closely with product, engineering, design, and data science teams to define, track, and report on critical user experience metrics that drive product roadmap decisions.

• Simultaneously manage multiple research projects, ensuring adherence to timelines, scope, and quality standards for each initiative.

• Leverage AI tools to enhance research workflows, automate data processing, and support advanced analytical tasks, driving efficiency and innovation.

📝 Enhancement Note: The emphasis on "AI-focused domains" and "Utilize AI tools to streamline workflows" indicates a need for candidates to demonstrate not just analytical skills but also an understanding of how AI can augment research processes. This implies a forward-thinking approach to research operations and a proactive stance on adopting new technologies.

🎓 Skills & Qualifications

Education: Bachelor's degree in a relevant field such as Human-Computer Interaction, Psychology, Sociology, Statistics, Computer Science, or a related discipline.

Experience: Minimum of 5 years of professional experience in quantitative UX research, market research, or data analysis roles.

Required Skills:

• Proven expertise in designing, programming, and launching surveys using platforms like Qualtrics.

• Strong proficiency in quantitative data analysis, including descriptive and inferential statistics.

• Hands-on experience with statistical analysis software such as R, SPSS, or SAS.

• Demonstrated ability to perform thematic or trend analysis on diverse datasets.

• Exceptional skills in data visualization and translating complex data into clear, compelling stories for stakeholders.

• Experience in defining and tracking key user experience metrics.

• Proficiency in managing multiple research projects concurrently within defined timelines.

• Familiarity with leveraging AI tools to support research workflows and data analysis.

Preferred Skills:

• Experience researching developers, AI technologies, or the use of AI by developers.

• Background in engineering, computer science, statistics, or a closely related technical field.

• Proficiency with Python for data analysis and scripting.

• Familiarity with Human-Computer Interaction (HCI) principles and methodologies.

• Experience with advanced survey methodologies like MaxDiff and conjoint analysis.

📝 Enhancement Note: The preference for a background in engineering, computer science, or statistics, coupled with experience in Python and AI research, suggests that this role may involve more technical depth and potentially more complex data challenges than a standard UX research position. Candidates with a strong analytical and technical foundation will be highly competitive.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Demonstrate a track record of designing and executing quantitative research studies that directly informed product strategy and led to measurable improvements in user experience.

• Showcase examples of complex data analysis, highlighting your methodology, the tools used (e.g., R, SPSS, Qualtrics), and the statistical rigor applied.

• Include case studies that illustrate your ability to translate quantitative findings into clear, actionable insights and compelling data visualizations.

Process Documentation:

• Provide evidence of your workflow for survey design, from initial research questions to final survey programming and quality assurance.

• Illustrate your process for conducting statistical analysis, including data cleaning, model selection, and interpretation of results.

• Showcase your approach to synthesizing findings and creating effective communication materials (presentations, dashboards) for diverse audiences.

• Detail how you manage project timelines, scope, and stakeholder communication throughout the research lifecycle.

📝 Enhancement Note: Given the quantitative and analytical nature of this role, a portfolio demonstrating concrete examples of research projects, data analysis techniques, and the resulting impact is crucial. The ability to articulate the process behind the successful outcomes, not just the outcomes themselves, will be key. Highlighting experience with survey programming and statistical analysis tools will be essential.

💵 Compensation & Benefits

Salary Range: $55 - $70 per hour.

Benefits:

• Health insurance coverage

• Vision insurance coverage

• Dental insurance coverage

• 401(k) plan

• Paid vacation time

• Paid sick leave

Working Hours:

• Full-time, 40 hours per week. Given the remote nature, flexibility may be expected based on project needs and team collaboration, but a standard 40-hour work week is anticipated.

📝 Enhancement Note: The hourly rate of $55-$70/hr for a temporary role with 5+ years of experience is competitive for specialized quantitative research roles in the US. The benefits package, while standard for full-time employment, is notable for a temporary position, suggesting the client may be seeking a highly engaged and long-term temporary contributor.

🎯 Team & Company Context

🏢 Company Culture

Industry: Market Research / User Experience Research Services. User Research International operates as a consultancy, providing specialized research expertise to various clients.

Company Size: While exact numbers aren't provided, consulting firms often have flexible team structures, with project-based teams formed from a larger pool of specialists. The "Temporary" nature of this role implies a project-driven operational model.

Founded: Information not directly provided, but the company operates as a professional services firm specializing in UX research.

Team Structure:

• The Quantitative UX Researcher will likely be part of a project-specific team, reporting to a Senior Researcher or Project Lead at User Research International.

• Collaboration will extend to the client's product, engineering, design, and data science teams, requiring strong cross-functional communication skills.

Methodology:

• Data-driven decision-making is paramount, with a strong emphasis on rigorous quantitative analysis and statistical validity.

• User-centric design principles guide research, aiming to improve user experiences through data-informed product development.

• Agile research methodologies may be employed to ensure timely delivery of insights within project constraints.

Company Website: https://uriux.com

📝 Enhancement Note: As a research consultancy, User Research International likely prioritizes scientific rigor, analytical excellence, and client satisfaction. The culture is expected to be professional, collaborative, and focused on delivering high-quality, data-backed insights. The "AI-focused domains" mention indicates a commitment to staying at the forefront of research trends.

📈 Career & Growth Analysis

Operations Career Level: This role represents a mid-to-senior level position for a quantitative researcher, requiring significant independent work and a strong understanding of research methodologies and statistical analysis. As a temporary role, it offers intensive project-based experience rather than a traditional long-term career path within User Research International itself.

Reporting Structure: The researcher will report to a project lead or senior researcher at User Research International. They will also collaborate closely with stakeholders at the client organization, including product managers, engineers, and designers.

Operations Impact: The primary impact of this role is to provide critical, data-driven insights that directly influence product development decisions, improve user experience, and ultimately contribute to the success of the client's products, especially within the AI domain. The role bridges the gap between raw data and strategic product direction.

Growth Opportunities:

• Project-Specific Expertise: Gain deep experience in AI-focused research domains and with specific client challenges, enhancing specialized skill sets.

• Methodological Advancement: Opportunity to refine and apply advanced statistical techniques and survey methodologies (e.g., conjoint analysis) in real-world scenarios.

• Cross-Functional Collaboration: Develop stronger communication and collaboration skills by working with diverse teams (product, engineering, data science).

• Potential for Future Engagements: Successful performance in this temporary role could lead to future project opportunities with User Research International or its clients.

📝 Enhancement Note: While this is a temporary role, it offers significant growth in specialized quantitative research skills, particularly within emerging areas like AI. The emphasis on data analysis and storytelling with data provides a strong foundation for further career development in data science, product analytics, or advanced UX research.

🌐 Work Environment

Office Type: Fully remote. This role is designated as "TELECOMMUTE" and requires U.S. residency, indicating a distributed workforce.

Office Location(s): United States. The specific time zone (America/Chicago mentioned in metadata) suggests a potential preference for candidates within or near that zone for collaboration, but the remote nature allows for broader U.S. coverage.

Workspace Context:

• The work environment is highly independent and self-directed, requiring strong self-discipline and time management skills.

• Access to necessary software and analytical tools will be provided or expected, with a focus on digital collaboration platforms.

Work Schedule:

• Standard 40-hour work week is expected. While remote, adherence to project deadlines and availability for key meetings will be important. Some flexibility may be possible, but consistent availability during core working hours for collaboration is likely required.

📝 Enhancement Note: The remote, temporary nature of this role necessitates a high degree of autonomy and self-management. Candidates should be comfortable working independently, managing their own schedule, and actively communicating to stay connected with their team and project stakeholders.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A review of your resume and application, focusing on quantitative research experience, statistical skills, and proficiency with required tools (Qualtrics, R/SPSS/SAS).

• Technical Interview: Likely involves discussions about your experience with survey design, statistical analysis, data visualization, and potentially coding challenges or problem-solving scenarios related to data interpretation. Expect questions on how you've applied specific methodologies.

• Portfolio Review: You will be asked to present examples from your portfolio showcasing your quantitative research projects, data analysis techniques, and the impact of your findings. Be prepared to walk through your process and highlight your contributions.

• Behavioral/Cultural Fit Interview: Assess your ability to collaborate with cross-functional teams, communicate complex ideas clearly, manage multiple projects, and adapt to client needs, particularly in an AI context.

Portfolio Review Tips:

• Quantify Everything: For each project, clearly state the research objectives, your specific role, the methodologies used, the sample size, and most importantly, the quantifiable results and impact achieved.

• Showcase Data Storytelling: Include examples of compelling data visualizations and presentations that effectively communicated insights to non-technical stakeholders.

• Highlight Process: Be ready to explain your step-by-step process for survey design, data analysis, and reporting. Emphasize your quality assurance measures.

• Tailor to AI: If possible, include projects related to AI, technology, or complex data analysis that demonstrate your ability to tackle challenging, modern research problems.

• Demonstrate Tool Proficiency: Clearly indicate which tools you used for each project (Qualtrics, R, SPSS, SAS, Python, visualization tools).

Challenge Preparation:

• Be prepared for a case study or a live data analysis exercise. Practice designing a survey for a hypothetical product or feature, identifying key metrics, and outlining an analysis plan.

• Review common statistical tests and their applications. Understand how to interpret results from methods like MaxDiff or conjoint analysis.

• Brush up on your data storytelling skills – practice explaining technical findings in simple, business-oriented terms.

📝 Enhancement Note: The emphasis on quantitative skills and a portfolio review suggests that practical demonstration of abilities is key. Candidates should be ready to dive deep into their past work, explaining the 'how' and 'why' behind their analytical approaches and ensuring they can articulate the business value of their research.

🛠 Tools & Technology Stack

Primary Tools:

• Survey Programming: Qualtrics (required). Proficiency in designing complex survey logic, branching, and quotas.

• Statistical Analysis: R, SPSS, or SAS (required). Deep understanding of statistical modeling, hypothesis testing, and data manipulation.

• Data Visualization: Tools used for creating charts, graphs, and dashboards (e.g., Tableau, Power BI, or visualization libraries within R/Python).

• AI Tools: General familiarity with AI tools for workflow streamlining and data analysis support.

Analytics & Reporting:

• Experience with tools for analyzing user behavior data, potentially including analytics platforms for web or product usage.

CRM & Automation:

• While not explicitly mentioned, an understanding of how user research data integrates with CRM systems or influences product automation strategies can be beneficial.

📝 Enhancement Note: Proficiency in Qualtrics and at least one major statistical package (R, SPSS, SAS) is non-negotiable. Experience with Python is a strong plus, especially for data manipulation and advanced analysis. The mention of "AI tools" is broad, suggesting openness to using AI for efficiency rather than requiring specific AI platform expertise.

👥 Team Culture & Values

Operations Values:

• Data-Driven Rigor: A commitment to scientific accuracy, statistical validity, and evidence-based insights in all research endeavors.

• User-Centricity: A deep understanding of user needs and behaviors that drives impactful product improvements.

• Efficiency & Scalability: Focus on optimizing research processes and workflows to deliver timely and valuable insights, especially within project-based engagements.

• Collaborative Problem-Solving: A willingness to work closely with diverse teams to tackle complex challenges and co-create solutions.

• Adaptability & Innovation: Embracing new tools and methodologies, particularly in rapidly evolving fields like AI, to stay at the cutting edge of research.

Collaboration Style:

• Expect a highly collaborative environment where researchers work closely with client teams. This involves active listening, clear communication of complex findings, and a willingness to integrate feedback.

• Asynchronous communication (email, Slack, project management tools) will be common due to the remote nature, but synchronous meetings will be essential for key discussions and presentations.

• A culture of shared learning and knowledge exchange is likely, especially within User Research International's internal team.

📝 Enhancement Note: The values reflect a professional, analytical, and client-focused approach. For this temporary role, demonstrating your ability to integrate quickly into a client's team, understand their specific operational challenges, and contribute to their goals effectively will be important.

⚡ Challenges & Growth Opportunities

Challenges:

• Project Scope & Timelines: Managing multiple demanding projects simultaneously under tight deadlines requires excellent organizational and prioritization skills.

• Data Complexity: Working with potentially large and complex datasets, especially in AI domains, may require advanced analytical techniques and problem-solving.

• Translating Technical Findings: Effectively communicating sophisticated statistical results and AI-related nuances to non-technical stakeholders is a key challenge.

• Remote Collaboration: Maintaining strong communication and collaboration in a fully remote, temporary capacity requires proactive engagement and clear articulation.

Learning & Development Opportunities:

• Specialized Domain Knowledge: Gain in-depth experience researching AI technologies and their user impact, a rapidly growing field.

• Methodological Mastery: Deepen expertise in advanced quantitative methods like conjoint analysis and complex statistical modeling.

• Cross-Disciplinary Exposure: Work closely with product managers, engineers, and data scientists, broadening understanding of product development lifecycles.

• Consulting Skills: Develop client management and communication skills through project-based engagements.

📝 Enhancement Note: The challenges are typical for a senior-level researcher but are amplified by the temporary nature and the cutting-edge domain. Focusing on your ability to quickly adapt, learn, and deliver high-impact results under pressure will be key.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you designed and launched a complex survey. What were the key challenges, and how did you ensure data quality?" (Focus on Qualtrics, sampling, and QA processes).

• "Walk me through an example of a complex statistical analysis you performed. What was the problem, your methodology, the tools you used (R, SPSS, SAS), and the actionable insights you derived?" (Emphasize your analytical process and interpretation).

• "How do you approach translating quantitative findings into a compelling story for product and engineering teams?" (Prepare examples of data visualizations and presentation narratives).

Company & Culture Questions:

• "Why are you interested in a temporary role focused on quantitative UX research, particularly in AI domains?" (Connect your skills and interests to the role's specifics).

• "How do you manage your time and prioritize tasks when working on multiple projects simultaneously?" (Highlight your organizational and project management skills).

Portfolio Presentation Strategy:

• Structure Your Case Studies: For each project, clearly outline: Problem/Objective -> Your Role -> Methodology -> Key Findings -> Impact/Recommendations.

• Visuals are Key: Showcase your best data visualizations. Be prepared to explain what makes them effective and how they communicate complex information.

• Quantify Impact: Whenever possible, use metrics to demonstrate the business impact of your research (e.g., "identified issues leading to a X% improvement in task completion," "insights informed a feature that increased user engagement by Y%").

• Tool Transparency: Clearly state the tools and techniques used in each project.

• Conciseness: Be mindful of time during your presentation. Focus on the most impactful projects and insights.

📝 Enhancement Note: The interview process will heavily scrutinize your quantitative skills and your ability to communicate complex data effectively. Prepare specific examples that demonstrate your proficiency with required tools and methodologies, and be ready to articulate the business value of your work.

📌 Application Steps

To apply for this operations position:

• Submit your application through the provided application link.

• Portfolio Customization: Curate your portfolio to prominently feature quantitative UX research projects, emphasizing survey design, statistical analysis (R, SPSS, SAS), data visualization, and impact. Include case studies with clear methodologies and measurable outcomes.

• Resume Optimization: Tailor your resume to highlight keywords such as "Quantitative UX Researcher," "Survey Design," "Statistical Analysis," "Data Visualization," "Qualtrics," "R," "SPSS," "SAS," "AI Research," and "User Experience Metrics." Quantify achievements wherever possible.

• Interview Preparation: Practice articulating your research process, statistical methodologies, and how you translate data into actionable insights. Prepare to discuss your experience with AI tools and your ability to manage multiple projects remotely.

• Company Research: Familiarize yourself with User Research International's services and client base. Understand the importance of quantitative research in informing product strategy, particularly within technology and AI sectors.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

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