UX Researcher II (Quant Focused)

📍 Job Overview

Job Title: UX Researcher II (Quant Focused)

Company: Smartsheet

Location: Bellevue, WA, USA

Job Type: Full-Time

Category: User Experience Research / Product Insights

Date Posted: May 22, 2026

Experience Level: Mid-Level (3-5 years)

Remote Status: Hybrid (Office in Bellevue, WA) or Fully Remote within the US

🚀 Role Summary

• Drive strategic product impact by leading end-to-end quantitative and qualitative research initiatives.

• Influence product strategy and near-term design improvements through comprehensive data analysis and user insights.

• Leverage descriptive and inferential statistics, including R or Python, to analyze behavioral and survey data at scale.

• Collaborate closely with Product Design and cross-functional teams to inform product roadmaps and user-centered design practices.

• Apply a diverse set of research methodologies, adapting to the needs of rapid, 'scrappy' studies and in-depth, comprehensive research.

📝 Enhancement Note: This role is specifically looking for a UX Researcher with a strong quantitative focus, integrating statistical analysis with research methodologies. The "II" in the title suggests a mid-level position requiring demonstrated experience in driving impact and influencing strategy, rather than just executing research tasks. The remote option within the US is a key flexibility point.

📈 Primary Responsibilities

• Strategic Impact & Roadmap Development: Identify research questions and priorities without guidance, contributing to the creation of a holistic research roadmap that aligns with product pillars and strategic objectives.

• End-to-End Research Execution: Independently plan, design, and conduct mixed-methods research studies (generative and evaluative) to address complex product and design challenges.

• Quantitative Data Analysis: Utilize descriptive and inferential statistics to analyze behavioral data, telemetry logs, and survey results. Identify significant trends, patterns, and user sentiment to inform product decisions.

• Insight Generation & Communication: Translate complex data and research findings into actionable, strategic insights that elevate the team's understanding of user needs and behaviors.

• Influence Product Strategy: Proactively influence product priority and strategy, in addition to driving near-term design and product improvements, by providing well-supported recommendations.

• Methodology Adaptation: Flexibly apply a wide range of research methodologies, from rapid, agile approaches to comprehensive, in-depth studies, based on the specific research questions and project timelines.

• Cross-Functional Collaboration: Build strong, trust-based relationships with Product Design, Product Management, Engineering, and other cross-functional partners, serving as the go-to research expert for assigned product areas.

• AI Literacy Integration: Understand and articulate the implications of AI tools in data processing and synthesis, including potential risks like bias and hallucinations, within research findings and recommendations.

📝 Enhancement Note: The responsibilities highlight a progression from tactical execution to strategic influence, emphasizing the ability to impact product direction rather than just user experience. The prompt's focus on AI literacy is a modern and critical addition for contemporary UX research roles.

🎓 Skills & Qualifications

Education:

• Bachelor's or Master's degree in a related field such as Psychology, Human-Computer Interaction (HCI), Anthropology, Communication, Design, Statistics, or equivalent practical experience. Experience:

• 3-5 years of professional experience in User Experience (UX) Research or a closely related field, with a demonstrable track record of impacting product development. Required Skills:

• Quantitative Research Expertise: Proven experience designing and executing quantitative research studies, including surveys and behavioral data analysis.

• Statistical Proficiency: Strong understanding and practical application of descriptive and inferential statistics.

• Data Analysis Tools: Hands-on experience using statistical software like R or Python for data manipulation, analysis, and visualization of large datasets (e.g., telemetry, behavioral logs, complex surveys).

• Mixed-Methods Research: Proficiency in a variety of generative (e.g., interviews, ethnographic studies) and evaluative (e.g., usability testing, A/B testing analysis) research methods.

• Insight Synthesis: Ability to synthesize findings from multiple data sources and methodologies into clear, actionable, and strategic insights.

• Communication & Presentation: Excellent verbal and written communication skills, with the ability to tailor presentations and insights to diverse audiences (e.g., designers, product managers, executives).

• AI Literacy: Foundational understanding of how AI tools process and synthesize data, awareness of potential risks such as bias and hallucinations.

Preferred Skills:

• Experience within a SaaS (Software as a Service) product environment.

• Familiarity with product analytics platforms (e.g., Amplitude, Mixpanel, Google Analytics).

• Experience contributing to product strategy discussions and influencing product roadmaps.

• Knowledge of experimental design and A/B testing methodologies.

• Experience working with product teams in an agile development environment.

📝 Enhancement Note: The emphasis on R/Python for data analysis is a significant differentiator for this role, pointing towards a highly analytical UX research position. The "AI Literacy" requirement is a forward-thinking addition.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Quantitative Case Studies: Showcase 2-3 detailed case studies demonstrating your experience with quantitative UX research. This should include:

  • Clear problem statements and research objectives.
  • Methodologies employed (e.g., surveys, A/B test analysis, telemetry analysis, experimental design).
  • Rigorous analytical approaches using statistical methods (mentioning R/Python where applicable).
  • Quantifiable impact of your insights on product decisions, feature development, or user experience improvements.
  • Examples of how you measured user sentiment or behavior at scale.

• Mixed-Methods Integration: Illustrate instances where you've combined quantitative findings with qualitative data to provide a more holistic understanding of user behavior and needs.

• Strategic Impact Examples: Include projects where your research directly influenced product strategy, roadmap prioritization, or significant design iterations, demonstrating your ability to drive business outcomes.

• System Awareness: While not a primary focus, briefly touch upon your experience working within common product development systems and tools (e.g., Jira, Confluence) that facilitate research operations.

Process Documentation:

• Research Planning: Demonstrate your ability to document research plans, including clear research questions, hypotheses, participant criteria, and methodological choices.

• Analysis Methodology: Provide examples of how you document your data analysis process, including statistical techniques used, data cleaning steps, and interpretation of results.

• Insight Reporting: Showcase how you document and present research findings, ensuring clarity, conciseness, and actionable recommendations for product and design teams.

📝 Enhancement Note: Given the quantitative focus, the portfolio is expected to heavily feature data-driven case studies, statistical analysis, and demonstrated impact on product strategy. The emphasis is on the process of research and analysis, not just the outcomes.

💵 Compensation & Benefits

Salary Range: $110,000 - $143,750 USD per year.

Benefits:

• Health & Wellness:

  • Employer-subsidized medical, vision, and dental coverage for full-time employees.
  • Counseling membership for mental well-being.

• Financial Security:

  • 401k match (50% of your contribution up to the first 6% of eligible pay) to support retirement savings.
  • Company-sponsored life insurance, short-term disability, and long-term disability plans.

• Work-Life Balance:

  • Flexible Time Away Program, plus Sick Time Off.
  • 12 paid holidays per year.
  • Up to 24 weeks of Parental Leave.
  • Personal paid Volunteer Day to support community involvement.

• Productivity & Development:

  • Monthly stipend to support your work and productivity.
  • Opportunities for professional growth and development, including access to Udemy online courses.
  • Your own personal Smartsheet account for practice and exploration.

• Perks:

  • Local retail discounts. Working Hours:

• Standard full-time work week, typically 40 hours. The role offers flexibility in how these hours are structured, especially for remote employees, provided project deadlines and team collaboration needs are met.

📝 Enhancement Note: The salary range is provided and is competitive for a mid-level UX Researcher in a tech hub like Bellevue, WA. The benefits package is extensive, covering health, financial, and work-life balance aspects, with a notable monthly stipend for productivity.

🎯 Team & Company Context

🏢 Company Culture

Industry: Software / Productivity Tools / Work Management (SaaS)

Company Size: Smartsheet is a well-established, publicly traded company, indicating a robust organizational structure and significant market presence. This size typically means established processes, opportunities for specialized roles, and cross-functional interaction.

Founded: Over 20 years ago, suggesting a mature company with a proven track record and a stable foundation.

Team Structure:

• UX Research Team: This team is part of the broader Product Design organization, working closely with Product Designers, Product Managers, and Engineers. Researchers are embedded within product teams or focus on specific product pillars/experiences.

• Reporting Structure: The role reports to a UX Manager, indicating a hierarchical structure within the UX team that allows for mentorship and guidance.

• Cross-functional Collaboration: A core aspect of the role involves deep collaboration with Product Design, Product Management, and Engineering teams, requiring strong communication and partnership skills.

Methodology:

• Human-Centered Design: Smartsheet emphasizes human-centered design principles, with UX Research playing a pivotal role in understanding user needs and translating them into intuitive and valuable experiences.

• Data-Driven Insights: The company values data-driven decision-making, making the quantitative skills of this role particularly crucial for informing product direction.

• Agile Development: Likely operates within an agile development framework, requiring researchers to adapt their methodologies to fast-paced iterative cycles.

Company Website: https://www.smartsheet.com/

📝 Enhancement Note: Smartsheet's established nature suggests a professional environment with opportunities for significant impact on a widely used product. The emphasis on human-centered and data-driven design aligns perfectly with the requirements of this UX Research role.

📈 Career & Growth Analysis

Operations Career Level: UX Researcher II (Mid-Level). This level signifies a professional who can operate with significant autonomy on feature-level and pillar-level projects, contributing to strategic discussions and influencing product direction. They are expected to mentor junior researchers and lead complex research initiatives.

Reporting Structure: Reports to a UX Manager, providing opportunities for mentorship, skill development feedback, and career path discussions. This manager likely oversees a portfolio of UX research specialists.

Operations Impact: The role has a direct impact on product strategy, feature development, and overall user experience. By providing data-driven insights, the UX Researcher helps shape the product's roadmap, ensuring it meets user needs and maintains a competitive edge. The quantitative focus means impact is often measured through metrics related to user adoption, task success, satisfaction, and retention.

Growth Opportunities:

• Specialization: Deepen expertise in quantitative research methodologies, statistical analysis (R/Python), or specific product areas.

• Leadership: Progress to a Senior UX Researcher role, leading larger, more complex research initiatives, mentoring junior team members, and taking on more strategic product ownership.

• Management: Potential to move into a UX Research Manager role, overseeing a team of researchers, defining research strategy, and managing stakeholder relationships.

• Cross-functional Mobility: Opportunities to leverage research skills in related areas like Product Management or Data Science, depending on individual interests and development.

• Skill Development: Access to Udemy courses, internal workshops, and mentorship programs to continuously enhance research skills, statistical capabilities, and understanding of AI's role in product development.

📝 Enhancement Note: The "II" designation implies a defined growth path. The quantitative focus suggests opportunities to become a subject matter expert in this area, which is highly valued in SaaS companies.

🌐 Work Environment

Office Type: Smartsheet offers a hybrid work model, with an office presence in Bellevue, WA. This suggests a collaborative office environment for those who choose to work from there, with opportunities for in-person brainstorming, team meetings, and relationship-building.

Office Location(s): Bellevue, Washington, USA. This is a major technology hub, offering a vibrant ecosystem of tech companies and professionals.

Workspace Context:

• Collaborative Environment: The hybrid model allows for flexible collaboration. In-office days likely involve team syncs, whiteboarding sessions, and informal knowledge sharing. Remote work provides focused, uninterrupted time for deep analysis and report writing.

• Operations Tools & Technology: Access to standard professional tools (e.g., company laptops, software licenses) and specific UX research tools. The emphasis on R/Python suggests a robust technical infrastructure is available.

• Team Interaction: Opportunities for regular interaction with Product Design, Product Management, and Engineering teams through scheduled meetings, async communication channels (e.g., Slack), and project-specific collaborations.

Work Schedule:

• While a standard 40-hour work week is expected, Smartsheet offers flexibility. This allows researchers to manage their time effectively, balancing deep analytical work with collaborative sessions, and accommodating different working styles and personal needs, especially for remote employees.

📝 Enhancement Note: The hybrid and remote-friendly nature of the role caters to modern work preferences, balancing in-person collaboration with the focused work often required for quantitative analysis.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter or hiring manager will review your application and resume to assess basic qualifications and experience.

• Hiring Manager Interview: A discussion with the UX Manager to delve deeper into your experience, research philosophy, and alignment with the team's needs. This is where your quantitative skills will be explored.

• Portfolio Review & Presentation: A dedicated session where you will present 1-2 key case studies from your portfolio, focusing on your quantitative research process, analysis, and impact. Be prepared to discuss your methodology, statistical approach, and how your insights informed product decisions.

• Cross-functional Interviews: Interviews with other UX researchers, Product Designers, or Product Managers to assess your collaboration skills, communication style, and ability to integrate into the team.

• Skills Assessment (Potential): You might be asked to complete a take-home assignment or a live coding/analysis exercise to demonstrate your proficiency with R/Python and statistical analysis.

• Final Interview: Potentially with a senior leader in Product or Design to discuss strategic thinking and overall fit.

Portfolio Review Tips:

• Quantify Everything: For your quantitative case studies, clearly articulate the data sources, the statistical methods used (e.g., t-tests, regression, ANOVA, descriptive stats), and how you interpreted the results. Use charts and graphs effectively.

• Show, Don't Just Tell Impact: Demonstrate the tangible outcomes of your research. Did your findings lead to a measurable increase in conversion rates, task completion, or user satisfaction? Quantify this impact if possible.

• Storytelling with Data: Weave a narrative around your research projects. Explain the problem, your process, the challenges you faced, how you overcame them, and the ultimate impact.

• Highlight R/Python Usage: Explicitly mention and, if possible, show examples of how you used R or Python to analyze data. Be ready to discuss your approach to data cleaning, analysis, and visualization.

• AI Literacy Examples: If you have experience or thoughts on incorporating AI in research or analyzing AI-driven features, be prepared to discuss this.

Challenge Preparation:

• Statistical Concepts: Refresh your understanding of common statistical concepts and their application in UX research.

• R/Python Practice: Practice data manipulation, statistical analysis, and visualization using R or Python. Be ready to discuss your preferred libraries and workflows.

• Hypothetical Scenario: Prepare to discuss how you would approach a hypothetical research problem with a quantitative bent.

📝 Enhancement Note: The interview process strongly emphasizes the quantitative aspects of UX research. Preparing a portfolio that clearly showcases statistical analysis and the use of R/Python is critical.

🛠 Tools & Technology Stack

Primary Tools:

• Statistical Analysis & Programming: R, Python (with libraries like Pandas, NumPy, SciPy, Statsmodels, Scikit-learn).

• Data Visualization: Tools within R/Python (e.g., ggplot2, Matplotlib, Seaborn), potentially BI tools like Tableau or Power BI.

• Survey Platforms: Qualtrics, SurveyMonkey, Google Forms, or internal tools for designing and deploying surveys.

• Usability Testing Platforms: UserTesting.com, Lookback, Maze, or internal tools for remote and in-person testing.

• Collaboration & Project Management: Jira, Confluence, Asana, or similar tools for tracking research projects and documentation.

Analytics & Reporting:

• Product Analytics: Amplitude, Mixpanel, Google Analytics, or similar platforms for understanding user behavior within the product.

• Telemetry/Behavioral Logs: Experience working with raw log data to extract user interaction patterns.

• Reporting Tools: Ability to create clear, concise reports and dashboards (e.g., in Google Slides, PowerPoint, or BI tools) to communicate findings.

CRM & Automation:

• While not a direct CRM role, an understanding of how user data is managed within CRM systems (like Salesforce) and how automation impacts user journeys might be beneficial for context.

📝 Enhancement Note: The explicit mention of R and Python is a strong indicator of the required technical stack. Proficiency in these languages for data analysis is paramount.

👥 Team Culture & Values

Operations Values:

• Customer Centricity: A deep commitment to understanding and advocating for the user. Insights are used to ensure the product genuinely solves user problems and provides value.

• Data-Driven Decision Making: A strong emphasis on using data – both quantitative and qualitative – to inform product decisions and validate hypotheses.

• Collaboration & Partnership: Valuing strong working relationships with Product Design, Product Management, and Engineering to ensure research insights are effectively integrated into the product development lifecycle.

• Impact & Ownership: Taking initiative and ownership of research projects, driving them to completion, and ensuring their insights lead to meaningful product improvements.

• Curiosity & Continuous Learning: Fostering an environment where team members are encouraged to explore new methodologies, stay updated on industry trends (including AI), and share knowledge.

Collaboration Style:

• Embedded Partnership: Researchers are often embedded within product teams, working closely and daily with designers and PMs.

• Data-Sharing Culture: Openness to sharing data, findings, and methodologies across the UX and product teams.

• Constructive Feedback: A culture that encourages giving and receiving constructive feedback on research plans, methodologies, and findings to improve the quality and impact of the work.

• Agile Iteration: Collaboration is iterative, with research feeding into design sprints and product development cycles.

📝 Enhancement Note: The company's emphasis on data-driven decisions and cross-functional partnership aligns perfectly with the requirements of a quantitative UX Researcher who needs to influence product strategy.

⚡ Challenges & Growth Opportunities

Challenges:

• Balancing Depth and Breadth: Effectively managing a research roadmap that includes both deep, strategic quantitative studies and more rapid, tactical evaluative research.

• Data Integration Complexity: Synthesizing insights from diverse data sources (telemetry, surveys, interviews, usability tests) to create a cohesive user understanding.

• Influencing Without Authority: Persuading stakeholders and product teams to act on research findings, especially when they challenge existing assumptions or priorities.

• Keeping Pace with AI: Understanding and integrating the implications of AI features into research methodologies and product strategy, while navigating potential ethical and technical challenges.

• Remote Collaboration Effectiveness: Ensuring seamless communication and collaboration with cross-functional teams when working remotely or in a hybrid capacity.

Learning & Development Opportunities:

• Advanced Statistical Training: Opportunities to deepen expertise in statistical modeling, machine learning, and advanced data analysis techniques relevant to UX research.

• AI in UX Research: Dedicated learning paths or workshops on how to research AI-powered features and leverage AI tools responsibly within the research process.

• Product Strategy Influence: Gaining experience in contributing to higher-level product strategy discussions and roadmap planning.

• Methodological Expansion: Learning and applying new research techniques, potentially including more qualitative methods if desired, to complement quantitative strengths.

• Mentorship Programs: Access to mentorship from senior researchers or UX leaders within Smartsheet.

📝 Enhancement Note: The "challenges" section is framed to highlight areas where the candidate can demonstrate problem-solving skills and a proactive approach to development, directly linking to growth opportunities.

💡 Interview Preparation

Strategy Questions:

• Quantitative Research Design: "Describe a time you designed a quantitative study to answer a complex product question. What was your hypothesis, what methodology did you choose, and why? How did you ensure the validity and reliability of your data?" (Prepare to discuss your R/Python approach here.)

• Data Analysis & Insights: "Walk us through a project where you analyzed large datasets (e.g., telemetry, survey data) using R or Python. What were the key insights, and how did you communicate them to drive product decisions?"

• Influencing Product Strategy: "Tell us about a situation where your research findings challenged the existing product direction or a team's assumptions. How did you present your findings, and what was the outcome?"

• AI Literacy Application: "How do you see AI impacting UX research in the next few years? What are the ethical considerations you'd keep in mind when researching AI-powered features?"

Company & Culture Questions:

• Smartsheet's Product: "What are your thoughts on Smartsheet's product? How do you see UX research contributing to its continued success?" (Research the product beforehand!)

• Collaboration Style: "Describe your ideal working relationship with Product Designers and Product Managers. How do you ensure research is integrated effectively into their workflow?"

• Measuring Impact: "How do you measure the success and impact of your UX research initiatives?"

Portfolio Presentation Strategy:

• Focus on Quantitative Case Studies: Select 1-2 projects that prominently feature your quantitative skills, statistical analysis, and use of R/Python.

• Structure Your Narrative: For each case study, clearly outline:

  1. The Problem: What was the business or user challenge?
  2. Your Role & Objectives: What were you tasked to do?
  3. Methodology: Detail the quantitative methods used.
  4. Analysis: Explain your statistical approach (mention R/Python).
  5. Key Findings: Present the most impactful insights.
  6. Recommendations & Impact: What actions were taken, and what was the quantifiable outcome?

• Be Prepared for Details: Expect questions about your statistical choices, data handling, and interpretation of results. Demonstrate a deep understanding of the "why" behind your choices.

• Visual Aids: Use clear, concise slides with effective data visualizations. Avoid overwhelming your audience with raw data; focus on insights.

📝 Enhancement Note: The interview process will heavily scrutinize the candidate's quantitative skills. Practicing discussions around statistical methods and demonstrating the application of R/Python in portfolio examples is crucial.

📌 Application Steps

To apply for this UX Researcher II (Quant Focused) position:

• Submit your application through the Smartsheet careers portal via the provided job link.

• Tailor Your Resume: Highlight your 3-5 years of UX research experience, specifically emphasizing quantitative methodologies, your proficiency with R/Python for data analysis, and any experience with AI literacy or product strategy influence. Quantify achievements wherever possible.

• Curate Your Portfolio: Select 2-3 strong case studies that showcase your quantitative research process, statistical analysis skills (including R/Python usage), and demonstrable impact on product decisions. Ensure your portfolio is easily accessible (e.g., a personal website, PDF).

• Prepare Your Presentation: Practice presenting your chosen portfolio case studies, focusing on clarity, conciseness, and your ability to articulate complex quantitative findings and their strategic implications. Be ready for potential live analysis or scenario-based questions.

• Research Smartsheet: Understand Smartsheet's product, its target audience, and its market position. Familiarize yourself with their company values and recent news to tailor your responses and demonstrate genuine interest.

⚠️ 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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