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: 2026-04-07

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

Remote Status: Remote OK (US-based)

🚀 Role Summary

• Drive strategic product impact through quantitative UX research, influencing feature-level decisions and holistic experience design.

• Execute end-to-end research initiatives, adapting methodologies to both rapid and in-depth study requirements.

• Elevate team knowledge by translating tactical findings into strategic insights that inform product priority and roadmap.

• Leverage statistical analysis (R/Python) of behavioral and survey data to identify significant trends and user sentiment at scale.

• Collaborate closely with Product Design and cross-functional teams to champion user-centered design principles and inform product development.

📝 Enhancement Note: This role is specifically focused on quantitative UX research, emphasizing data analysis, statistical proficiency, and the ability to influence product strategy through measurable insights. While qualitative methods are implied, the "Quant Focused" title and the explicit mention of R/Python and descriptive/inferential statistics highlight a strong leaning towards data-driven decision-making.

📈 Primary Responsibilities

• Lead the identification and prioritization of research questions, developing comprehensive research roadmaps in collaboration with Product Design partners.

• Design and execute a variety of quantitative research studies, including surveys, A/B tests, and analysis of telemetry/behavioral data, to understand user needs and product usage patterns.

• Apply descriptive and inferential statistical techniques to analyze large datasets, uncovering statistically significant trends, correlations, and patterns.

• Synthesize complex quantitative findings into clear, actionable, and strategic recommendations for product improvements and future development.

• Clearly articulate research findings, limitations, and implications to diverse stakeholders, including product managers, designers, engineers, and leadership.

• Contribute to the development of user intuition across the product team and leverage competitive analysis to identify opportunities for product differentiation.

• Stay abreast of emerging AI technologies and their implications for data analysis, user behavior, and potential risks like bias and hallucinations.

• Proactively build and maintain strong, trust-based relationships with product, design, and engineering teams, establishing yourself as a key research resource.

📝 Enhancement Note: The responsibilities emphasize a proactive and strategic approach to research, moving beyond task execution to influencing product direction. The expectation to adapt methodologies and handle both rapid and in-depth studies suggests a dynamic research environment.

🎓 Skills & Qualifications

Education:

Experience:

• 3-5 years of progressive experience in User Experience (UX) Research or a closely related field.

Required Skills:

• Quantitative Research Expertise: Proven ability to design, conduct, and analyze quantitative UX research, including surveys, behavioral data analysis, and A/B testing.

• Statistical Analysis: Strong proficiency in descriptive and inferential statistics.

• Programming for Data Analysis: Practical experience using statistical programming languages such as R or Python for data manipulation, analysis, and visualization of large datasets.

• Methodological Versatility: Experience with a range of generative and evaluative research methods, with the ability to select and adapt them appropriately for different research questions.

• Data Synthesis & Insight Generation: Ability to translate raw data into meaningful, actionable insights that drive product decisions.

• Communication & Presentation: Excellent verbal and written communication skills, with the ability to tailor presentations and findings to various audiences.

• AI Literacy: Understanding of AI tools, data processing capabilities, and potential risks like bias and hallucinations.

Preferred Skills:

• Experience with telemetry data and behavioral logs analysis.

• Familiarity with data visualization tools and techniques.

• Experience working in an Agile development environment.

• Understanding of product development lifecycles and cross-functional team dynamics.

• Experience with user sentiment analysis at scale.

📝 Enhancement Note: The emphasis on R/Python and statistical analysis is a critical differentiator for this role, indicating a need for a researcher who can deeply engage with quantitative data and complex datasets. The "AI Literacy" requirement is also a forward-thinking addition.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Showcase at least 2-3 projects that highlight your quantitative research skills and impact.

• For each project, clearly articulate the research objectives, methodologies used (especially quantitative), and the specific statistical analyses performed.

• Detail the insights derived from the data and how these insights directly influenced product decisions, design iterations, or strategic direction.

• Demonstrate your ability to handle complex datasets, including telemetry, behavioral logs, or large-scale survey data.

Process Documentation:

• Prepare to discuss your personal research process, including how you approach problem definition, methodology selection, data collection, analysis, and reporting for quantitative studies.

• Be ready to explain how you adapt your research process based on project constraints (e.g., time, resources) and the specific research questions.

• Provide examples of how you ensure the rigor and validity of your quantitative research findings.

📝 Enhancement Note: A strong portfolio demonstrating quantitative research skills, statistical analysis, and data-driven impact is crucial. Candidates should be prepared to walk through their projects and explain their quantitative methodologies and the business outcomes achieved.

💵 Compensation & Benefits

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

Explanation: This range is provided by the company and reflects the mid-level experience requirement (3-5 years), the specialized quantitative focus, and the location in a major tech hub like Bellevue, WA.

Benefits:

• Health & Wellness:

  • Medical, vision, and dental coverage options for full-time employees.
  • Counseling membership and other company-funded perks for mental well-being.

• Financial Security:

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

• Work-Life Balance:

  • Flexible Time Away Program and Sick Time Off to support personal needs.
  • 12 paid holidays per year.
  • Up to 24 weeks of Parental Leave.
  • Personal paid Volunteer Day to contribute to the community.

• Professional Development:

  • Monthly stipend to support work and productivity.
  • Opportunities for professional growth and development, including access to Udemy online courses.

• Other Perks:

  • Local retail discounts.

Working Hours:

• Standard full-time hours, typically around 40 hours per week.

• The role offers teleworking options from any registered US location, providing flexibility around work hours and location.

📝 Enhancement Note: The salary range is competitive for a mid-level UX Researcher with strong quantitative skills in a high-cost-of-living area like Bellevue. The benefits package is comprehensive, with a strong emphasis on health, financial security, and professional development, which are often attractive to operations and research professionals.

🎯 Team & Company Context

🏢 Company Culture

Industry: Software / Work Management Solutions

Company Size: Smartsheet is a well-established company in the SaaS space, likely employing over 1,000 individuals based on typical industry growth for successful platforms. This size suggests a structured but agile environment with opportunities for impact.

Founded: Over 20 years ago, indicating a mature company with a proven track record and a stable market presence.

Team Structure:

• The UX Research team is part of the broader Product Design function, reporting to a UX Manager.

• Researchers work closely with Product Designers, Product Managers, and Engineers, forming cross-functional product teams.

Methodology:

• Smartsheet emphasizes human-centered design principles and data-driven decision-making.

• The UX Research team is expected to lead critical research efforts, providing insights to inform design and product development.

• There's a focus on both tactical (feature-level) and strategic (holistic experience) impact.

• The team balances rapid, "scrappy" approaches with comprehensive, in-depth studies.

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

📝 Enhancement Note: Smartsheet's established presence and focus on "achieving anything" and "magic at work" suggest a culture that values ambition, innovation, and employee empowerment. The emphasis on collaboration within cross-functional teams is typical for successful SaaS companies.

📈 Career & Growth Analysis

Operations Career Level: This role is positioned as a UX Researcher II, indicating a mid-level individual contributor role. It requires a solid foundation in research methodologies and the ability to work independently on defined projects, while also beginning to influence broader product strategy.

Reporting Structure: The role reports to the UX Manager. This provides a clear reporting line for guidance, mentorship, and career development discussions. The researcher will likely be embedded within specific product teams, collaborating closely with Product Managers and Designers.

Operations Impact: The UX Researcher plays a vital role in shaping Smartsheet's product by ensuring user needs are understood and addressed. The quantitative focus means this role will directly impact product decisions by providing data-backed evidence for design choices, feature prioritization, and overall product strategy. This influence contributes to user satisfaction, adoption rates, and ultimately, business growth.

Growth Opportunities:

• Skill Specialization: Deepen expertise in quantitative research methodologies, statistical analysis (R/Python), and potentially advanced areas like causal inference or predictive modeling.

• Strategic Influence: Progress to influencing product strategy at a higher level, potentially leading research for major product initiatives or pillars.

• Mentorship & Leadership: As experience grows, opportunities may arise to mentor junior researchers or lead cross-functional research initiatives.

• Cross-Functional Mobility: Develop strong relationships with Product Management and Design, potentially leading to opportunities in those areas if desired.

• Industry Advancement: Gain experience with a leading SaaS platform, enhancing marketability and providing a strong foundation for future roles in UX research or product.

📝 Enhancement Note: The "II" designation suggests a step beyond entry-level, with expectations for greater autonomy and strategic contribution. The growth path clearly points towards increasing influence and specialization within the quantitative UX research domain.

🌐 Work Environment

Office Type: The position can be based in their Bellevue, WA office or be fully remote within the US. This offers flexibility depending on candidate preference and location.

Office Location(s):

Workspace Context:

• Hybrid/Remote Flexibility: The option for remote work suggests a modern, trust-based work environment that accommodates diverse working styles and locations.

• Collaborative Environment: As part of cross-functional product teams, the researcher will engage in frequent collaboration with designers, product managers, and engineers, likely utilizing digital collaboration tools.

• Tools & Technology: Access to industry-standard research tools, analytics platforms, and the Smartsheet platform itself for conducting and documenting work.

Work Schedule:

• Full-time, standard business hours (approximately 40 hours/week).

• The remote option provides flexibility in managing work hours, though core collaboration times with US-based teams will need to be considered.

📝 Enhancement Note: The hybrid/remote option is a significant benefit, catering to a modern workforce. The emphasis on cross-functional collaboration within product teams is standard for efficient product development in tech companies.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter will likely review applications and conduct an initial screening call to assess basic qualifications, experience, and cultural fit.

• Hiring Manager Interview: An interview with the UX Manager to delve deeper into your research experience, methodologies, and strategic thinking.

• Portfolio Review & Presentation: A key stage where you will present a selection of your quantitative research projects. Expect to discuss your process, findings, impact, and how you leveraged tools like R/Python.

• Cross-Functional Interviews: Interviews with Product Managers, Product Designers, or Engineers to assess your collaboration skills, ability to translate insights into action, and understanding of product development.

• Final Interview: Potentially with a more senior leader to discuss overall fit and strategic alignment.

Portfolio Review Tips:

• Quant Focus: Select projects that prominently feature your quantitative research skills, statistical analysis, and data-driven insights.

• Impact Stories: For each project, clearly articulate the problem, your approach (especially the quantitative methods), the key findings, and the tangible impact on the product or business. Use metrics where possible.

• Tool Proficiency: Be prepared to discuss your experience with R, Python, and other relevant data analysis or survey tools. Show code snippets or analysis outputs if appropriate and anonymized.

• Methodological Rationale: Explain why you chose specific quantitative methods and what their limitations were.

• Clear Communication: Practice presenting your findings concisely and engagingly, ensuring that complex statistical concepts are understandable to a non-expert audience.

Challenge Preparation:

• Be prepared for a potential take-home assignment or a live case study exercise focused on analyzing a dataset or designing a quantitative research plan for a given product scenario.

• Practice articulating your thought process for problem-solving, data interpretation, and recommending solutions based on quantitative evidence.

• Think about how you would approach a research problem at Smartsheet specifically, considering their product and user base.

📝 Enhancement Note: The portfolio review will be critical, with a strong emphasis on quantitative skills. Candidates should prepare to demonstrate not just what they did, but how they did it quantitatively and the business results they achieved.

🛠 Tools & Technology Stack

Primary Tools:

• Quantitative Analysis: R, Python (essential), potentially SQL for data extraction.

• Survey Platforms: Tools like SurveyMonkey, Qualtrics, or specialized UX survey tools for designing and deploying surveys.

• Data Visualization: Tools like Tableau, Power BI, or libraries within R/Python (e.g., ggplot2, Matplotlib, Seaborn) for creating dashboards and reports.

• Statistical Software: Beyond R/Python, familiarity with SPSS, SAS, or JASP could be beneficial.

Analytics & Reporting:

• Telemetry/Product Analytics: Tools like Amplitude, Mixpanel, Google Analytics, or internal logging systems to analyze user behavior within the product.

• Reporting Tools: Smartsheet itself for project management and reporting, plus standard office suites for presentations.

CRM & Automation:

• While not directly a CRM/automation role, understanding how user data flows from CRM or marketing automation platforms into product analytics can be beneficial.

📝 Enhancement Note: Proficiency in R and Python for data analysis is a non-negotiable requirement for this "Quant Focused" role. Experience with survey tools and product analytics platforms is also highly relevant.

👥 Team Culture & Values

Operations Values:

• Data-Driven Decision Making: A core value, emphasizing the use of quantitative evidence to guide product strategy and design.

• Customer Centricity: A commitment to understanding and advocating for user needs through rigorous research.

• Collaboration & Partnership: Working effectively within cross-functional teams to achieve shared goals.

• Impact & Ownership: Taking responsibility for research outcomes and driving meaningful change.

• Continuous Learning: Staying current with research methodologies, tools, and industry trends.

Collaboration Style:

• Cross-Functional Integration: Researchers are expected to be active participants in product teams, seamlessly integrating with Product Managers and Designers.

• Data Sharing & Transparency: Findings and insights are shared openly to foster a collective understanding of the user.

• Constructive Feedback: An environment where feedback is exchanged constructively to improve research quality and product outcomes.

• Agile Approach: Comfort working in iterative cycles, with the ability to adapt research plans quickly based on team needs and product velocity.

📝 Enhancement Note: The culture at Smartsheet, as described, values a blend of analytical rigor and collaborative spirit. The emphasis on data-driven decisions and customer advocacy aligns perfectly with the quantitative UX Researcher role.

⚡ Challenges & Growth Opportunities

Challenges:

• Balancing Speed and Rigor: Adapting quantitative research techniques to deliver timely insights for fast-paced product development cycles without sacrificing scientific validity.

• Data Complexity: Managing and analyzing large, potentially messy datasets from various sources (telemetry, surveys, etc.) to extract clear, actionable insights.

• Influencing Diverse Stakeholders: Effectively communicating complex quantitative findings and recommendations to audiences with varying levels of data literacy and product involvement.

• AI Integration: Navigating the ethical considerations and practical applications of AI in research and product development, particularly concerning data bias and output reliability.

Learning & Development Opportunities:

• Advanced Statistical Techniques: Opportunities to deepen knowledge in areas like causal inference, predictive modeling, or experimental design.

• New Tool Proficiency: Learning and applying new data analysis, visualization, or AI-assisted research tools.

• Product Strategy Contribution: Growing influence to shape product roadmaps and long-term strategy through impactful research.

• Cross-Functional Expertise: Gaining a deeper understanding of product management, design, and engineering processes.

• Industry Conferences & Training: Access to professional development resources to stay at the forefront of UX research trends.

📝 Enhancement Note: The challenges presented are typical for a quantitatively focused researcher in a dynamic tech environment. The growth opportunities are well-aligned with advancing expertise in data analysis and strategic product influence.

💡 Interview Preparation

Strategy Questions:

• Quantitative Approach: "Describe a complex product problem you solved using quantitative UX research. What was your approach, what tools did you use (e.g., R/Python), what were the key statistical findings, and what was the business impact?"

• Methodology Adaptation: "How do you decide between different quantitative research methods (e.g., survey vs. behavioral analysis vs. A/B test) for a given research question? Provide an example."

• Data Interpretation: "Imagine you found a statistically significant correlation between Feature X usage and user retention. How would you investigate further to understand the causal relationship and inform product decisions?"

Company & Culture Questions:

• Smartsheet's Product: "What are your thoughts on Smartsheet's product and its current UX? How might you approach researching a new feature for it?"

• Collaboration: "Describe a time you had to work closely with Product Managers and Designers on a research project. How did you ensure alignment and integrate their perspectives with your quantitative findings?"

• Data Ethics: "How do you approach potential biases in quantitative data, especially when dealing with user behavior or AI-generated insights?"

Portfolio Presentation Strategy:

• Quant-Centric Narrative: For each presented project, emphasize the quantitative aspects: hypothesis, data sources, statistical methods, key metrics, and data-driven conclusions.

• Tool Demonstration (if applicable): Be ready to briefly show or describe how you used R/Python for analysis, perhaps walking through a visualization or a statistical test.

• Impact & ROI: Clearly articulate the business impact of your research. Quantify it with metrics if possible (e.g., "led to a 15% increase in task completion," "informed a design change that reduced support tickets by 10%").

• Conciseness: Stick to the key elements of each project, focusing on the problem, your quantitative solution, and the outcome.

📝 Enhancement Note: Preparation should focus heavily on showcasing quantitative skills, statistical literacy, experience with R/Python, and the ability to translate data into actionable product strategy. Demonstrating an understanding of Smartsheet's product and user base will also be beneficial.

📌 Application Steps

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

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

• Portfolio Customization: Curate your portfolio to prominently feature 2-3 projects showcasing your quantitative research expertise, statistical analysis skills (especially R/Python), and measurable impact.

• Resume Optimization: Tailor your resume to highlight keywords related to quantitative UX research, statistical analysis, R, Python, behavioral data analysis, survey design, and strategic product influence. Quantify achievements with data and impact metrics.

• Interview Preparation: Practice articulating your quantitative research process, methodology choices, and the insights/impact of your past projects. Be ready to discuss your experience with R/Python and statistical concepts.

• Company Research: Familiarize yourself with Smartsheet's product, target audience, and company values. Consider how your quantitative research skills can directly contribute to their mission.

⚠️ 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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