Senior Quantitative UX Researcher

📍 Job Overview

Job Title: Senior Quantitative UX Researcher

Company: Trustpilot

Location: Edinburgh, Scotland, United Kingdom

Job Type: Full-time

Category: User Experience Research / Data & Analytics

Date Posted: 2026-09-14T07:56:38

Experience Level: Mid-Senior Level (4+ years)

Remote Status: Hybrid

🚀 Role Summary

• Lead and own the quantitative research roadmap for specific product areas, driving strategic product decisions through rigorous data analysis and user insights.

• Design and execute large-scale surveys, behavioral analytics, and experimentation to measure user trust and guide product development.

• Establish and maintain high standards for statistical rigor across the UX research team, in close collaboration with Data Science.

• Translate complex quantitative findings into clear, actionable narratives for product managers, designers, and engineers, fostering a data-driven product culture.

• Pioneer and critically evaluate the use of AI-assisted techniques in research, ensuring validity and mitigating bias.

📝 Enhancement Note: This role is positioned as a Senior Quantitative UX Researcher, indicating a need for leadership in research strategy, execution, and mentorship within the quantitative domain. The emphasis on "owning the quantitative research roadmap" and "setting the bar for statistical rigour" suggests a significant level of autonomy and influence.

📈 Primary Responsibilities

• Design, implement, and manage the quantitative research roadmap for assigned product areas, focusing on attitudinal measurement, behavioral analysis, and longitudinal tracking.

• Lead the execution of large-scale surveys, including the design of validated scales, NPS derivatives, and trust-perception metrics.

• Conduct in-depth log-data and behavioral analytics, including funnel analysis, A/B test design and interpretation, and cohort/retention modeling.

• Develop and maintain robust measurement frameworks to define and track key performance indicators related to user trust and journey progression (e.g., review reading, purchase decisions, business subscriptions).

• Lead advanced quantitative research initiatives, employing statistical rigor in areas such as experimental design, predictive modeling, and psychometric validation.

• Spearhead the application of AI-assisted techniques (e.g., LLM-assisted open-text analysis) for research enhancement, with a critical assessment of validity and bias.

• Collaborate closely with Data Science and Analytics teams to ensure alignment on shared definitions, data pipelines, and measurement strategies.

• Act as a guardian of study design and statistical rigor, upholding high standards across the entire UX research team.

• Translate complex statistical outputs and data-driven findings into clear, compelling, and decision-forcing narratives for product stakeholders.

• Coach and mentor other UX researchers in quantitative methodologies, enhancing the team's overall statistical literacy through pairing and constructive feedback.

• Partner with Product Managers, Designers, and Engineers to integrate quantitative insights into the product development lifecycle, ensuring actionable recommendations are implemented.

📝 Enhancement Note: The responsibilities highlight a blend of strategic ownership, hands-on execution, and team enablement. The emphasis on "owning the quantitative research roadmap" and "partnering with Data Science" suggests a strategic, cross-functional role. Coaching other researchers indicates a senior-level expectation for mentorship and knowledge sharing.

🎓 Skills & Qualifications

Education: While not explicitly stated, a Bachelor's or Master's degree in a quantitative field such as Psychology, Statistics, Computer Science, Economics, Sociology, or a related discipline is highly recommended. Advanced degrees are often preferred for senior-level research roles involving complex methodologies.

Experience: 4+ years of dedicated UX research experience with a strong, demonstrated specialization in quantitative research methodologies and the execution of complex, broad-scope projects.

Required Skills:

• Proven expertise in designing and executing quantitative UX research studies, including large-scale surveys and behavioral analysis.

• Strong command of survey methodology, encompassing instrument design, sampling strategies, and psychometric validation principles.

• Solid statistical grounding, with hands-on experience in regression analysis, factor/cluster analysis, and significance testing.

• Proficiency in at least one scripting language for data analysis, such as Python, R, or SQL, with direct experience working with large behavioral datasets.

• Direct experience with behavioral analytics platforms (e.g., Amplitude, Looker, BigQuery) and extracting insights from user interaction data.

• A demonstrable track record of quantitative research that has measurably influenced product or business decisions.

• Hands-on experience with A/B testing methodologies, including experimental design, execution, and analysis of results.

• Practical experience experimenting with AI tools in a research workflow (e.g., LLM-assisted open-text analysis, AI-assisted qualitative coding) with a critical eye on validity and bias.

• Excellent communication and interpersonal skills, capable of effectively collaborating with diverse, cross-functional teams (Product, Design, Engineering, Data Science).

• Ability to present data-driven findings in an engaging, accessible, and decision-forcing manner to both technical and non-technical audiences. Preferred Skills:

• Experience with longitudinal tracking and building measurement frameworks.

• Familiarity with predictive modeling techniques.

• Experience working within a fast-paced, high-growth tech environment.

• A critical and curious mindset regarding AI's capabilities and limitations in research contexts.

• Experience in coaching or mentoring junior researchers.

• Familiarity with product analytics and business intelligence tools beyond those listed as required.

📝 Enhancement Note: The requirements emphasize deep quantitative expertise and practical application. The specific mention of Python/R/SQL and platforms like Amplitude/Looker/BigQuery points to a hands-on role requiring technical proficiency. The inclusion of AI experimentation reflects a forward-thinking approach to research methodologies.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Demonstrable case studies showcasing the design and execution of complex quantitative UX research projects.

• Evidence of building and owning quantitative research roadmaps for specific product areas.

• Examples of creating and implementing measurement frameworks for key user journeys and business objectives.

• Detailed documentation of survey design, including sampling strategies and validation methods.

• Work samples illustrating the application of statistical analysis (e.g., regression, factor analysis) to user data.

• Case studies detailing A/B test design, execution, and the impact of findings on product decisions.

• Examples of translating complex data into clear, actionable insights and recommendations for product teams.

• Documentation of experience with large behavioral datasets and relevant analytics tools (Amplitude, Looker, BigQuery). Process Documentation:

• Showcase of workflow design for quantitative research projects, from initial problem definition to final reporting.

• Evidence of establishing and maintaining data pipelines for behavioral analytics.

• Examples of rigorous study design documentation, including hypotheses, methodologies, and analysis plans.

• Documentation of how quantitative findings were integrated into product development cycles and decision-making processes.

• Examples of process improvements implemented in research methodologies or data analysis techniques.

📝 Enhancement Note: For a Senior Quantitative UX Researcher, the portfolio should heavily emphasize the strategic ownership of research initiatives, the rigor of quantitative methodologies employed, and the tangible business impact derived from their work. The ability to demonstrate process ownership and improvement is crucial.

💵 Compensation & Benefits

Salary Range: For a Senior Quantitative UX Researcher in Edinburgh, Scotland, with 4+ years of experience, the estimated salary range is £65,000 - £85,000 per annum. This estimate is based on industry benchmarks for similar roles in the UK tech sector, considering the specialized quantitative skills and the seniority of the position. Factors influencing the exact offer include specific experience, the candidate's negotiation skills, and the overall compensation structure of Trustpilot.

Benefits:

• Flexible working options to support work-life balance.

• Competitive compensation package, reflecting the senior nature of the role.

• Performance-based bonus.

• Generous annual leave: 25 days, increasing to 28 days after 2 years of service.

• Two paid volunteering days per year to contribute to community causes.

• Comprehensive learning and development opportunities through the Trustpilot Academy and external resources like Blinkist.

• Company pension scheme.

• Life insurance coverage.

• Health cash plan for routine medical expenses.

• Access to an online GP service for convenient medical consultations.

• 24/7 Employee Assistance Program (EAP) for confidential support.

• Subscription to Headspace, a popular mindfulness and mental well-being app.

• Paid parental leave, supporting new parents.

• Season ticket loan to assist with commuting costs.

• Cycle-to-work scheme, promoting sustainable commuting.

• Access to a wide range of employee discounts and deals.

Working Hours: The standard working hours are approximately 40 hours per week, with flexibility offered to support work-life balance. This aligns with typical full-time employment in the UK tech industry.

📝 Enhancement Note: The salary range is an estimation based on current market data for similar roles in Edinburgh. The benefits package is extensive and aligns with what is expected for a senior role in a reputable tech company, offering strong support for employee well-being and professional development.

🎯 Team & Company Context

🏢 Company Culture

Industry: Online Reviews Platform / Software as a Service (SaaS) - Trustpilot operates in the dynamic and competitive digital space, providing a critical service for both consumers and businesses by fostering transparency and trust through customer reviews. This industry context means a focus on data integrity, user experience, and scalable technology solutions.

Company Size: Trustpilot is a FTSE-250 listed company with over 1000 employees, indicating a large, established organization with significant market presence. This size suggests a structured environment with opportunities for career advancement, but also the need for clear processes and efficient operations to maintain agility.

Founded: Trustpilot was founded in 2007. This history indicates a mature company that has successfully navigated market changes and scaled its operations, now operating globally with a strong brand reputation.

Team Structure:

• The UX Research team likely operates within a Product or Engineering division, consisting of a mix of qualitative and quantitative researchers. Given the role's seniority, this Senior Quantitative UX Researcher will likely lead the quantitative efforts for their product area and may manage or mentor other researchers.

• Collaboration is expected across Product Management, UX Design, Data Science, and Engineering teams, requiring strong cross-functional communication and influence.

• The reporting structure would likely place the researcher under a Head of UX Research or a Director of Product, with direct interaction with Product Managers and Designers for their specific product domains. Methodology:

• Data-Driven Decision Making: A core methodology, emphasized by the need for quantitative rigor and collaboration with Data Science. Insights are expected to be grounded in empirical evidence.

• Agile Product Development: Likely integrated within agile sprints, requiring researchers to provide timely insights to support iterative product development cycles.

• User-Centric Design: While this role is quantitative, the ultimate goal is to improve the user experience of Trustpilot's platform, ensuring that data insights serve user needs.

• Continuous Improvement: The company's emphasis on "disrupting ourselves through innovation, data and insight" suggests a culture of ongoing learning, experimentation, and process optimization.

Company Website: https://corporate.trustpilot.com/

📝 Enhancement Note: Trustpilot's status as a FTSE-250 company implies a certain level of organizational maturity and structure. The emphasis on "disrupting ourselves" suggests a culture that values innovation and proactive change, which is important for a researcher focused on driving impact.

📈 Career & Growth Analysis

Operations Career Level: This role is classified as "Senior," indicating a level of expertise and responsibility beyond entry or mid-level positions. A Senior Quantitative UX Researcher is expected to operate with a high degree of autonomy, lead complex research initiatives, mentor junior colleagues, and significantly influence product strategy through their quantitative insights. This level often involves defining best practices and contributing to the overall research strategy of the team.

Reporting Structure: The Senior Quantitative UX Researcher will likely report to a Head of UX Research, Director of Product, or a similar senior leader within the product organization. They will work closely with Product Managers, UX Designers, and Data Scientists within their assigned product domain, forming a core cross-functional team.

Operations Impact: The impact of this role is directly tied to improving user trust and experience on the Trustpilot platform, which in turn drives engagement, subscription rates for businesses, and overall platform growth. By rigorously measuring user behavior and perceptions, this researcher will provide critical data that informs product roadmaps, feature prioritization, and strategic business decisions, ultimately contributing to Trustpilot's mission of becoming the universal symbol of trust.

Growth Opportunities:

• Leadership in Quantitative Research: Potential to become the go-to expert or lead for quantitative UX research within Trustpilot, setting standards and driving innovation.

• Mentorship & Team Development: Opportunities to coach and mentor junior researchers, developing leadership skills and contributing to the growth of the research practice.

• Specialization in AI/ML for Research: Deepen expertise in applying emerging AI and ML techniques to UX research challenges, a highly valuable and growing field.

• Cross-functional Influence: Grow influence across Product, Engineering, and Data Science teams, shaping broader business strategy based on user insights.

• Career Progression: Potential advancement to Lead UX Researcher, Principal UX Researcher, or management roles within the research or product organization.

📝 Enhancement Note: The "Senior" title implies a significant impact on product strategy and the potential for leadership. Growth opportunities are tied to deepening expertise in quantitative methods, AI, and influencing cross-functional teams, typical for senior operational roles in tech.

🌐 Work Environment

Office Type: Trustpilot operates a hybrid work model, with a central office located in Edinburgh. This suggests a modern, collaborative workspace designed to facilitate team interaction, brainstorming, and in-person collaboration when needed, while still offering the flexibility of remote work.

Office Location(s): The primary office for this role is in Edinburgh, Scotland. The description mentions "Central office location," implying it's easily accessible within the city, likely with good public transport links. Trustpilot also has offices in other global locations, indicating a distributed but connected workforce.

Workspace Context:

• Collaborative Environment: The office is described as having "pop up events organised by our own community team as well as the building’s community team," suggesting a vibrant social and professional atmosphere. Regular team socials and company-wide celebrations foster a sense of community.

• Tools and Technology: Researchers will have access to the necessary software and hardware for quantitative analysis, including potentially powerful workstations, access to analytics platforms, and collaboration tools. The role explicitly mentions proficiency in Python/R/SQL and platforms like Amplitude/Looker/BigQuery, indicating these are available or supported.

• Team Interaction: The hybrid model allows for structured in-person collaboration with product teams (PMs, Designers, Engineers) and Data Scientists, while also accommodating focused individual work remotely.

Work Schedule: The role is full-time, with approximately 40 working hours per week. The hybrid model and flexible working options mean that while core hours may exist for team collaboration, there's likely flexibility in how and when the 40 hours are structured, accommodating deep work and personal needs.

📝 Enhancement Note: The hybrid model and emphasis on community events suggest a company culture that values both focused work and social connection, a common trait in modern tech companies aiming to balance productivity with employee well-being.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A brief call with a recruiter to assess basic qualifications, experience, and cultural fit.

• Hiring Manager Interview: A deeper dive with the hiring manager (likely Head of UX Research or similar) to discuss your experience, approach to quantitative research, and alignment with the role's strategic objectives.

• Technical/Portfolio Review: A session dedicated to reviewing your portfolio. This will involve presenting 1-2 key quantitative research case studies, detailing your process, methodologies, findings, and impact. Be prepared to discuss your statistical reasoning, tool proficiency, and how you translated data into actionable insights.

• Cross-functional Interview: An interview with key stakeholders from Product Management, UX Design, and/or Data Science to assess your collaboration skills, ability to communicate complex findings, and how you integrate with product teams.

• Final Interview/Debrief: Potentially a final conversation with a senior leader or a debrief session to confirm fit and discuss next steps.

Portfolio Review Tips:

• Quantify Impact: Clearly articulate the business or product impact of your quantitative research. Use metrics and data to demonstrate how your work led to tangible improvements or informed critical decisions.

• Showcase Process Rigor: For each case study, detail your methodology, including survey design, sampling strategy, statistical analysis techniques used, and any validation processes. Explain why you chose specific methods.

• Highlight Tool Proficiency: Naturally weave in your experience with Python/R/SQL, Amplitude, Looker, BigQuery, or other relevant tools. Demonstrate how you leveraged these tools to derive insights.

• Tell a Story: Structure your case studies as narratives: the problem, your approach, the data/analysis, the insights, and the outcome/recommendations.

• Address AI Critically: If you have experience with AI-assisted research, be prepared to discuss its application, your critical evaluation of its validity and potential biases, and how it enhanced your work.

• Tailor to Trustpilot: Research Trustpilot's platform, mission, and recent product developments. Frame your examples to show how your skills align with their specific needs and challenges related to trust and user experience.

Challenge Preparation:

• Data Interpretation: Be ready to interpret sample data sets or scenarios to identify trends, potential issues, and actionable insights.

• Methodology Design: You might be asked to outline a quantitative research approach for a given product problem, demonstrating your ability to design robust studies.

• Communication Skills: Practice explaining complex statistical concepts and research findings in simple, clear language suitable for non-technical stakeholders.

📝 Enhancement Note: The interview process is likely structured to assess not only technical quantitative skills but also strategic thinking, collaboration, and communication abilities. The portfolio review is critical, requiring candidates to demonstrate tangible impact and methodological rigor.

🛠 Tools & Technology Stack

Primary Tools:

• Statistical Analysis & Scripting: Python (with libraries like Pandas, NumPy, SciPy, Statsmodels), R (with libraries like dplyr, ggplot2, base R stats), SQL (for data extraction and manipulation from databases like BigQuery).

• Behavioral Analytics Platforms: Amplitude, Google Analytics, or similar tools for tracking user funnels, events, and user journeys.

• Data Warehousing/Databases: Experience with querying large datasets, likely from platforms like Google BigQuery, Snowflake, or similar.

• Survey Platforms: Tools for designing and deploying large-scale surveys (e.g., SurveyMonkey Enterprise, Qualtrics, Google Forms, custom-built solutions).

Analytics & Reporting:

• Data Visualization Tools: Tableau, Power BI, Looker, or custom dashboards built with libraries like Matplotlib/Seaborn (Python) or ggplot2 (R) for presenting findings.

• A/B Testing Tools: Experience with platforms like Optimizely, Google Optimize, or in-house experimentation frameworks.

• Reporting Dashboards: Ability to create and maintain dashboards for tracking key metrics and communicating performance to stakeholders.

CRM & Automation:

• While not the primary focus, familiarity with CRM systems (e.g., Salesforce) and marketing automation platforms can be beneficial for understanding the broader customer journey and data flow.

• Integration Tools: Understanding how different data sources and tools integrate is valuable, though not explicitly required.

📝 Enhancement Note: The core technical requirements revolve around data analysis and manipulation using scripting languages (Python/R/SQL) and experience with large behavioral datasets and analytics platforms. Proficiency in these areas is non-negotiable for this role.

👥 Team Culture & Values

Operations Values:

• Data-Driven: A commitment to grounding decisions and recommendations in robust quantitative evidence and statistical rigor.

• User-Centricity: A dedication to understanding and improving the user experience, ensuring that quantitative insights directly benefit users and contribute to Trustpilot's mission of trust.

• Impact-Oriented: A focus on delivering actionable insights that drive measurable product improvements and business outcomes.

• Collaboration: A strong emphasis on working effectively with cross-functional teams (Product, Design, Engineering, Data Science) to achieve shared goals.

• Continuous Learning & Curiosity: An eagerness to explore new methodologies, tools (including AI), and analytical techniques to enhance research quality and efficiency.

• Integrity & Rigor: Upholding high standards for research design, data analysis, and the ethical use of user data.

Collaboration Style:

• Cross-functional Integration: Actively embedding within product teams, working closely with PMs and Designers to understand their needs and provide timely, relevant quantitative insights.

• Partnership with Data Science: Building strong working relationships with Data Scientists and Analysts to leverage shared data infrastructure, define metrics, and ensure consistency in measurement.

• Knowledge Sharing: Proactively sharing findings, methodologies, and learnings with the broader research team and relevant stakeholders through presentations, documentation, and informal discussions.

• Constructive Feedback: Open to giving and receiving feedback on research designs, analyses, and communication to continuously improve the quality and impact of the work.

📝 Enhancement Note: The values reflect a blend of analytical rigor, user focus, and collaborative teamwork, essential for a quantitative researcher operating within a product development environment. The emphasis on "disrupting ourselves" suggests a culture that embraces change and innovation.

⚡ Challenges & Growth Opportunities

Challenges:

• Balancing Rigor with Speed: The need to maintain high statistical rigor while delivering insights within fast-paced product development cycles.

• Translating Complexity: Effectively communicating intricate statistical findings and their implications to non-technical stakeholders.

• Data Accessibility & Quality: Navigating potential challenges in accessing clean, reliable data and ensuring data integrity for analysis.

• Evolving AI Landscape: Staying abreast of rapid advancements in AI and ML and critically evaluating their applicability and validity within UX research.

• Influencing Without Authority: Driving product decisions based on quantitative insights, often requiring strong persuasion and collaboration skills to influence stakeholders.

Learning & Development Opportunities:

• Advanced Quantitative Methods: Opportunities to deepen expertise in areas like causal inference, experimental design, predictive modeling, and longitudinal analysis.

• AI & Machine Learning for Research: Structured learning to explore and apply AI/ML techniques for tasks like natural language processing of open-ended feedback, predictive user behavior, and advanced segmentation.

• Product Strategy Integration: Developing a deeper understanding of business strategy and how quantitative UX research directly contributes to overarching company goals.

• Mentorship & Leadership: Formal or informal opportunities to mentor junior researchers, lead research initiatives, and potentially contribute to team strategy.

• Industry Conferences & Certifications: Support for attending relevant conferences (e.g., UXPA, CHI, industry-specific data science/analytics events) and pursuing certifications in specialized areas.

📝 Enhancement Note: The challenges are typical for senior quantitative roles, focusing on the intersection of technical expertise, communication, and strategic influence. Growth opportunities are geared towards deepening specialized skills and expanding leadership capabilities.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you designed a quantitative research study to measure a complex user behavior or perception. What was your hypothesis, methodology, and what did you learn?" (Focus on rigor, methodology, and insight generation).

• "How do you ensure statistical validity and rigor in your quantitative research, especially when working with large, complex datasets?" (Highlight statistical grounding, validation techniques, and data integrity).

• "Walk me through a situation where your quantitative findings significantly influenced a product decision or business strategy. What was the impact?" (Emphasize demonstrable impact and storytelling of your research journey).

• "How do you approach building measurement frameworks for product areas, and what key metrics do you typically focus on?" (Demonstrate strategic thinking about ongoing measurement and KPIs).

• "How would you collaborate with a Product Manager and a UX Designer who are primarily focused on qualitative insights to integrate your quantitative findings?" (Showcase cross-functional collaboration and communication skills).

• "What are your thoughts on using AI/LLMs in UX research? How would you critically evaluate its outputs and ensure validity?" (Assess your critical thinking and forward-looking approach to AI). Company & Culture Questions:

• "What interests you specifically about Trustpilot and our mission to be the universal symbol of trust?" (Research Trustpilot's values, mission, and recent news).

• "How do you see quantitative UX research contributing to Trustpilot's goals?" (Connect your skills to the company's objectives).

• "Describe your experience working in a hybrid environment and how you maintain strong collaboration with remote and in-office colleagues." (Assess adaptability to hybrid work).

• "How do you approach coaching or mentoring other researchers in quantitative methods?" (Evaluate your leadership and knowledge-sharing capabilities). Portfolio Presentation Strategy:

• Focus on Impact: Select 1-2 projects that clearly demonstrate significant business or product impact. Quantify results wherever possible.

• Structure Your Narrative: For each project, clearly outline: the problem/question, your research objectives, the methodology (design, sample, analysis), key findings, actionable insights, and the resulting actions or outcomes.

• Highlight Your Role: Be explicit about your specific contributions, especially if it was a collaborative project.

• Showcase Technical Skills: Naturally integrate discussions about the tools and statistical methods you used, explaining why they were appropriate.

• Prepare for Q&A: Anticipate questions about your methodological choices, alternative approaches you considered, limitations of your study, and how you handled unexpected results.

• Be Concise and Engaging: Practice your presentation to ensure it's clear, engaging, and fits within the allocated time.

📝 Enhancement Note: The interview preparation advice focuses on demonstrating not just technical proficiency but also strategic thinking, impact, and collaborative ability, which are key for a senior role. The emphasis on AI evaluation is also a critical component.

📌 Application Steps

To apply for this Senior Quantitative UX Researcher position at Trustpilot:

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

• Curate Your Portfolio: Select 1-2 of your most impactful quantitative UX research projects. Ensure these examples clearly demonstrate your expertise in survey methodology, behavioral analytics, statistical rigor, and how your insights drove product or business decisions. Quantify the impact of your work with specific metrics.

• Tailor Your Resume: Optimize your resume to highlight your 4+ years of experience in quantitative UX research. Use keywords from the job description such as "quantitative research," "survey methodology," "statistical analysis," "Python/R/SQL," "behavioral analytics," and "A/B testing." Clearly list your proficiency with relevant tools and platforms.

• Prepare Your Presentation: Rehearse your portfolio presentation, focusing on telling a clear, concise, and compelling story about your research process, findings, and impact. Be ready to discuss your methodological choices and answer detailed questions about your work.

• Research Trustpilot: Familiarize yourself with Trustpilot's mission, values, product offerings, and recent company news. Understand how their commitment to trust translates into their product and user experience, and be prepared to articulate how your quantitative skills can contribute to this 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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