Principal UX Researcher

📍 Job Overview

Job Title: Principal UX Researcher

Company: Good Maven

Location: London, England, United Kingdom

Job Type: FULL_TIME

Category: User Experience Research / Data Science

Date Posted: 2026-04-27

Experience Level: 10+ Years (Principal Level)

Remote Status: Hybrid/Remote (United Kingdom)

🚀 Role Summary

• Lead the quantitative UX research agenda and strategy for Super's core product surfaces, including sports, gaming onboarding, international growth, and loyalty programs within a fast-paced technology environment.

• Serve as the foremost expert in measuring, modeling, and predicting user behavior at scale, driving product decisions through influence and evidence-based insights.

• Own the quantitative research roadmap, setting methodological standards, and championing the integration of AI/ML techniques for advanced user behavior analysis.

• Collaborate closely with Data Science, Product Analytics, and Business Intelligence teams to establish a shared measurement culture and bridge the gap between UX and business metrics.

📝 Enhancement Note: This role is positioned as a Principal Individual Contributor (IC), signifying a senior leadership role focused on technical expertise and strategic influence rather than people management. The emphasis on "leading through influence, methodology, and the quality of evidence" highlights the expectation for deep expertise and the ability to drive change within the organization. The company's focus on entertainment and fan-centric experiences suggests a dynamic and data-driven environment where UX research directly impacts millions of user interactions daily.

📈 Primary Responsibilities

• Design, execute, and own the quantitative UX research roadmap for key product areas, encompassing attitudinal measurement, behavioral analysis, and longitudinal tracking.

• Lead the design and analysis of large-scale surveys (n=1,000–50,000+) using psychometrically rigorous instruments such as validated scales, conjoint/MaxDiff, SUPR-Q, SUS, and custom NPS derivatives.

• Conduct log-data and behavioral analytics research, including funnel analysis, session replay interpretation, A/B and multivariate test design/analysis, event-based cohort studies, and retention modeling.

• Develop and maintain UX measurement frameworks, defining key performance indicators (KPIs) for acquisition, activation, engagement, and loyalty, and tracking these metrics over time.

• Champion mixed-methods integration by designing studies that scale qualitative insights with quantitative data and vice versa, creating comprehensive evidence packages.

• Pioneer the application of AI and ML techniques in quantitative research, including LLM-assisted open-text analysis, NLP-based sentiment classification, clustering for user segmentation, and predictive modeling of UX outcomes.

• Build and maintain automated survey analysis pipelines using Python, R, or SQL to generate repeatable and auditable outputs, significantly reducing manual processing time.

• Evaluate and deploy emerging quantitative research tooling, such as AI-powered survey platforms and automated analysis pipelines, critically assessing their validity and potential biases.

• Develop documentation and training materials to enable the broader research team to adopt AI-assisted quantitative techniques responsibly.

• Own Super's UX metrics framework and in-product survey tool, defining canonical product experience KPIs, establishing benchmarks, and publishing regular tracker reports for product, design, and leadership.

• Partner with Data Science, Business Intelligence, and Product Analytics to align on shared definitions, event taxonomies, and data pipelines.

• Build and maintain a quantitative research repository containing reusable instruments, validated scales, benchmark datasets, and analysis templates to accelerate future studies.

• Define and enforce quantitative research quality standards across the team, reviewing study designs, statistical approaches, and reported effect sizes for rigor and accuracy.

• Serve as the primary quantitative UX authority for the product organization, advising product managers, designers, and commercial leads on measurement approaches.

• Translate complex statistical outputs into clear, business-relevant narratives that drive decision-making, focusing on storytelling rather than just presenting p-values.

• Proactively identify measurement gaps and user behavior blind spots within the product organization and design studies to address them.

• Mentor 2–4 mid-level quantitative and mixed-methods researchers, enhancing statistical literacy through coaching and informal pairing.

📝 Enhancement Note: The breadth of responsibilities indicates a role that is both deeply technical and highly strategic, requiring the ability to not only execute complex research but also to build and evangelize measurement frameworks and best practices across the organization. The emphasis on AI/ML and automation points to a forward-thinking approach to research operations.

🎓 Skills & Qualifications

Education:

Experience:

• 8+ years of UX research experience with a deep specialization in quantitative methods, including at least 5 years in a product or technology company operating at significant scale.

• Demonstrated track record of quantitative research that measurably influenced product strategy, feature prioritization, or go-to-market decisions.

Required Skills:

• Expert-level proficiency in survey methodology: instrument design, sampling theory, quota setting, weighting, psychometric validation, and analysis of large-scale surveys.

• Strong statistical competency: regression (linear, logistic, multinomial), factor analysis, cluster analysis, conjoint/MaxDiff, significance testing, Bayesian inference, and effect size interpretation.

• Hands-on proficiency in at least one analytical language: Python (pandas, scipy, statsmodels, scikit-learn) or R (tidyverse, lavaan, survey package).

• Direct experience working with large behavioral datasets (clickstream, event logs, session data) and analytics platforms (Amplitude, Mixpanel, BigQuery, Looker, or similar).

• Experience with A/B testing methodology: experimental design, power calculations, sequential testing, interaction effects, and guardrail metrics.

• Data storytelling: Ability to translate complex statistical findings into clear, actionable narratives for diverse audiences.

• Proactive measurement architect: Ability to identify measurement gaps and design solutions proactively.

• AI-curious practitioner: Experience incorporating AI tools into quantitative workflows and critical understanding of their capabilities and limitations.

Preferred Skills:

• Familiarity with causal inference methods: difference-in-differences, instrumental variables, propensity score matching.

• Experience with experience sampling (ESM) methods or real-time behavioral tracking.

• Published or conference-presented research in a relevant academic or practitioner venue.

📝 Enhancement Note: The required experience level and specific technical proficiencies (Python/R, advanced statistical methods, behavioral data analysis) clearly define this as a senior, expert-level role. The "Skills & Mindset" section emphasizes soft skills crucial for a Principal IC, such as influencing without authority and proactive problem-solving, which are critical for driving impact in a large organization.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Demonstrable examples of quantitative UX research studies that directly influenced product strategy, feature prioritization, or go-to-market decisions, showcasing measurable impact.

• Case studies detailing the design and execution of large-scale surveys, including methodologies, analytical approaches, and key findings.

• Evidence of building and maintaining UX measurement frameworks or KPI dashboards that track user behavior over time.

• Documentation of experience with behavioral data analysis, including funnel analysis, cohort studies, and A/B test design and interpretation.

Process Documentation:

• Showcase of experience in establishing quantitative research quality standards, including study design review, statistical approach validation, and rigor assessment.

• Examples of creating automated analysis pipelines (e.g., using Python/R/SQL) for repeatable and auditable research outputs.

• Documentation of contributions to shared measurement cultures, including collaboration with data science, BI, and product analytics teams on definitions and data pipelines.

• Presentation of work on building research repositories, including reusable instruments, validated scales, and benchmark datasets.

📝 Enhancement Note: Candidates will need to present concrete examples of their quantitative research impact. The focus is on demonstrating the ability to not only conduct research but also to build scalable systems, establish best practices, and influence product strategy through rigorous data. The portfolio should highlight the candidate's ability to operate autonomously and drive significant initiatives.

💵 Compensation & Benefits

Salary Range:

Based on industry benchmarks for Principal UX Researchers in London with 8+ years of experience, a competitive salary range is estimated between £90,000 - £130,000 per annum. This estimate considers the role's seniority, technical demands, strategic impact, and the company's status as a global technology firm backed by major investors.

Benefits:

• Competitive Compensation reflective of a Principal IC level.

• Equity Participation.

• Comprehensive health and wellness programs (details not specified but standard for tech roles).

• Opportunities for professional development and continuous learning.

• Access to leading-edge technology and research tools.

• Collaborative work environment with cross-functional teams.

Working Hours:

• Standard full-time hours (approximately 40 hours per week), with flexibility expected given the global nature of the company and the importance of responsive analysis.

📝 Enhancement Note: The salary estimate is based on publicly available data for senior UX Research roles in London, factoring in the "Principal" title and the advanced technical requirements. The provided benefits of "Equity Participation" and "Competitive Compensation" are noted. The AI-generated estimate of 40 working hours is a standard assumption for full-time roles.

🎯 Team & Company Context

🏢 Company Culture

Industry: Technology (Entertainment, Fan-Centric Experiences, Sports Betting & Gaming)

Company Size: 5,000+ employees. This large size indicates a complex organizational structure with significant resources, established processes, and opportunities for specialized roles and cross-functional collaboration. For operations professionals, it means potential for impact within a large system, as well as the need for strong navigation and influencing skills.

Founded: The company has evolved from its origins, with significant investment and growth noted, particularly the Blackstone investment in 2019 and a refinancing in 2025. This suggests a company that is well-funded, ambitious, and undergoing continuous development and expansion.

Team Structure:

• The UX function likely includes a mix of quantitative and qualitative researchers, designers, and product analysts.

• This Principal role will report into a senior leader within the UX or Product organization, likely a Director or VP.

Methodology:

• Data-driven decision-making is paramount, with a strong emphasis on measuring and modeling user behavior at scale.

• Integration of quantitative and qualitative research methods to provide holistic insights.

• Adoption of AI and ML techniques to enhance research capabilities and efficiency.

• Focus on building robust measurement infrastructure and establishing clear KPIs.

• Commitment to high standards of compliance, safety, and responsibility.

Company Website: https://goodmaven.com/

📝 Enhancement Note: The company's industry and scale suggest a dynamic environment where data and user behavior are central to strategic decisions. The emphasis on growth, global expansion, and investment from major players like Blackstone indicates a company with significant ambition and resources, which translates to opportunities for impactful work in operations and research.

📈 Career & Growth Analysis

Operations Career Level: Principal Individual Contributor (IC). This level signifies a senior expert responsible for setting technical direction, driving complex initiatives, and influencing strategy through deep domain knowledge, rather than managing a team. The role is critical for establishing best practices and mentoring others.

Reporting Structure: The Principal UX Researcher will likely report to a senior leader such as a Director or VP of UX, Product, or Research. They will work closely with product managers, designers, data scientists, and engineers.

Operations Impact: The work directly informs decisions impacting millions of daily user interactions across core product surfaces. The insights generated will shape product strategy, feature prioritization, and user experience, with a direct link to business metrics like acquisition, activation, engagement, and loyalty. The role has the potential to build foundational measurement infrastructure that drives long-term business value.

Growth Opportunities:

• Technical Specialization: Deepen expertise in advanced quantitative methods, AI/ML applications in UX, and causal inference.

• Strategic Influence: Grow influence across the product organization, shaping research agendas and measurement strategies for new product initiatives.

• Mentorship & Leadership: Develop leadership skills by mentoring junior researchers and setting methodological standards for the entire UX team.

• Cross-functional Leadership: Lead measurement initiatives that span multiple product domains and departments, fostering a unified understanding of user behavior.

• Industry Recognition: Potential to contribute to industry best practices through publications or conference presentations.

📝 Enhancement Note: As a Principal role, the growth path is focused on deepening expertise and increasing strategic impact within the organization. The opportunity to build measurement infrastructure from the ground up is a significant growth driver. The company's focus on innovation and scale provides a fertile ground for developing cutting-edge research methodologies.

🌐 Work Environment

Office Type: Hybrid. The role is based in London, UK, but the company supports remote work within the UK, indicating a flexible approach to workplace structure.

Office Location(s): London, England, United Kingdom. This location is a major global hub for technology and finance, offering a vibrant professional ecosystem.

Workspace Context:

• Collaborative Environment: The role necessitates close collaboration with product managers, designers, data scientists, and engineers, suggesting a dynamic, team-oriented workspace whether in person or virtual.

• Tools & Technology: Access to advanced analytics platforms, behavioral data repositories, and potentially AI-powered research tools. The company is likely to provide necessary hardware and software for data analysis and research.

• Impactful Work: The opportunity to work on products that engage millions of users globally, providing a stimulating environment for researchers focused on driving significant impact.

Work Schedule: Standard full-time hours (approx. 40 hours/week) with flexibility to accommodate global team collaboration and critical data analysis needs. Expectation of responsiveness and proactive engagement.

📝 Enhancement Note: The hybrid model allows for flexibility while maintaining the need for in-person collaboration in London. The emphasis on cross-functional teams and data-driven work implies a professional, results-oriented environment.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A review of your application, resume, and portfolio by a recruiter to assess basic qualifications and alignment with the role.

• Hiring Manager Interview: A discussion with the hiring manager (likely a Director/VP of UX/Research) to delve into your experience, strategic thinking, and how you approach quantitative UX research challenges.

• Technical/Peer Interviews: Sessions with other researchers, data scientists, or product analysts to assess your technical skills, statistical knowledge, and ability to collaborate. This may involve discussing past projects in detail.

• Case Study/Take-Home Challenge: A practical exercise designed to evaluate your approach to a real-world research problem, including study design, data analysis, and presentation of findings. This is a critical component for a Principal role.

• Final Interview: A discussion with senior leadership to assess cultural fit, strategic vision, and overall impact potential.

Portfolio Review Tips:

• Quantify Impact: For each project, clearly articulate the problem, your role, the methodology used, the key insights, and most importantly, the measurable impact on product strategy or business outcomes. Use specific numbers and metrics.

• Showcase Technical Depth: Include examples of complex survey designs, statistical analyses (regression, cluster analysis, etc.), behavioral data analysis, and A/B test interpretation.

• Highlight AI/ML Integration: If applicable, showcase projects where you've used AI/ML tools or techniques for open-text analysis, segmentation, or predictive modeling.

• Demonstrate Storytelling: Present your findings in a narrative format, clearly explaining complex statistical concepts in a way that is accessible to non-technical stakeholders. Focus on the "so what?"

• Structure for Clarity: Organize your portfolio logically, perhaps by project type or impact area. Use clear headings, visuals, and concise explanations. Be prepared to walk through 2-3 key projects in detail.

Challenge Preparation:

• Understand the Domain: Familiarize yourself with the sports betting and gaming industry, common user behaviors, and potential UX challenges related to trust, risk, and engagement.

• Focus on Measurement: Anticipate challenges that require designing measurement strategies for complex user behaviors or product features.

• Methodological Rigor: Be prepared to justify your methodological choices, discuss potential biases, and outline how you would ensure statistical validity.

• AI/ML Application: Consider how AI tools could be leveraged to solve the challenge, but also be ready to discuss their limitations and ethical considerations.

• Communicate Clearly: Practice articulating your thought process, assumptions, and proposed solutions concisely and persuasively.

📝 Enhancement Note: The interview process will heavily weigh the candidate's ability to demonstrate tangible impact and strategic thinking. A strong portfolio that showcases technical expertise, data storytelling, and experience with advanced quantitative methods, including AI/ML, will be crucial. The case study is a key opportunity to prove practical application of skills.

🛠 Tools & Technology Stack

Primary Tools:

• Analytical Languages: Python (with libraries like pandas, scipy, statsmodels, scikit-learn) and/or R (with packages like tidyverse, lavaan, survey). Proficiency in at least one is required.

• SQL: Essential for querying large behavioral datasets.

• Statistical Software: While Python/R are primary, familiarity with dedicated statistical packages may be beneficial.

Analytics & Reporting:

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

• Data Warehousing/BI Tools: BigQuery, Looker, or similar for accessing and visualizing large datasets.

• Survey Platforms: Tools for designing and deploying large-scale surveys, potentially with AI-augmented features.

• A/B Testing Platforms: Experience with tools for designing and analyzing experiments.

CRM & Automation:

• While not the primary focus, understanding how UX metrics integrate with CRM or marketing automation data could be beneficial.

• Familiarity with automation tools for survey analysis pipelines (e.g., scripts in Python/R).

📝 Enhancement Note: The core technical stack revolves around data analysis and statistical modeling using Python/R and SQL, integrated with behavioral analytics and survey platforms. Candidates should be prepared to discuss their proficiency with specific tools and how they leverage them for large-scale quantitative research.

👥 Team Culture & Values

Operations Values:

• Data-Driven Decision Making: A core principle, emphasizing the use of rigorous quantitative evidence to guide product and business strategies.

• User-Centricity: A deep commitment to understanding and advocating for the user, translating complex behaviors into actionable insights.

• Innovation & Continuous Improvement: A drive to explore and adopt new methodologies, particularly AI/ML, and to build scalable, efficient research infrastructure.

• Collaboration & Transparency: Fostering a team environment where different disciplines (UX, Data Science, Product) work together, share findings openly, and build a collective understanding of users.

• Integrity & Responsibility: Adherence to high standards of compliance, safety, and ethical research practices, especially within a regulated industry.

Collaboration Style:

• Cross-functional Integration: The role requires seamless collaboration with Product Managers, Designers, Data Scientists, and Business Intelligence teams, acting as a bridge between user insights and business objectives.

• Influence Without Authority: Expectation to lead and guide through expertise, evidence, and clear communication, rather than direct reporting lines.

• Mentorship and Knowledge Sharing: A culture of elevating the skills of peers and junior team members through coaching, training, and sharing best practices.

• Proactive Problem Solving: Encouraging a mindset where team members identify potential issues or measurement gaps and proactively develop solutions.

📝 Enhancement Note: The culture appears to value intellectual rigor, proactive problem-solving, and collaborative innovation. For operations professionals, this means an environment where data accuracy, process efficiency, and cross-team alignment are highly prized.

⚡ Challenges & Growth Opportunities

Challenges:

• Measuring Complex Behavior: Quantifying nuanced user behaviors like trust, risk-taking, emotional engagement, and loyalty in a high-stakes environment.

• Scaling Research Infrastructure: Building robust, automated, and repeatable quantitative research processes and measurement frameworks from the ground up.

• Driving Adoption of New Methods: Championing and integrating advanced techniques like AI/ML into existing workflows and gaining buy-in from stakeholders.

• Influencing Senior Stakeholders: Effectively translating complex statistical findings into clear, compelling narratives that drive strategic decisions among product and business leaders.

• Navigating a Fast-Paced Environment: Adapting to rapid product development cycles and market changes while maintaining rigorous research standards.

Learning & Development Opportunities:

• Advanced Methodologies: Opportunity to deepen expertise in cutting-edge quantitative UX research techniques, AI/ML applications, and causal inference.

• Industry Leadership: Potential to become a recognized expert in quantitative UX research within the gaming/entertainment tech sector.

• Strategic Impact: Play a pivotal role in shaping the measurement strategy and user understanding for a rapidly growing global company.

• Mentorship: Formal and informal opportunities to mentor junior researchers and contribute to the development of the broader research team.

• Cross-Disciplinary Growth: Learning from and collaborating with Data Science and Product Analytics experts to broaden understanding of data ecosystems and business impact.

📝 Enhancement Note: The primary challenges lie in the complexity of the domain and the scale of operations, requiring advanced methodological skills and strong influencing capabilities. The growth opportunities are significant for an individual looking to become a thought leader in advanced quantitative UX research.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you used quantitative research to significantly influence product strategy or a key business decision. What was the impact?" (Focus on STAR method, quantifying impact, and clear articulation of your role.)

• "How would you approach building a comprehensive UX measurement framework for a new product feature? What KPIs would you prioritize and why?" (Demonstrate understanding of measurement design, linking UX to business goals, and prioritization.)

Company & Culture Questions:

• "Given our focus on sports betting and gaming, what are some unique quantitative UX challenges you anticipate, particularly around trust and engagement?" (Research the industry and common UX considerations.)

• "How do you collaborate with data scientists and product analysts to ensure alignment on measurement and avoid conflicting insights?" (Highlight your cross-functional collaboration style and data validation processes.)

Portfolio Presentation Strategy:

• Focus on Impact: For your chosen case studies, emphasize the business problem, your unique contribution, the methodology, key findings, and the quantifiable results.

• Explain Your 'Why': Be ready to articulate the rationale behind your methodological choices and how they addressed the research questions.

• Showcase Technical Skills: Be prepared to discuss your analytical approach, including specific statistical techniques and tools used.

• Tell a Story: Structure your presentations like a narrative – problem, approach, solution, outcome. Make it engaging and easy to follow for a diverse audience.

• Anticipate Questions: Think about potential questions regarding limitations, alternative approaches, or next steps for your projects.

📝 Enhancement Note: Interview preparation should focus on demonstrating a blend of deep technical expertise in quantitative methods and the strategic ability to translate data into actionable business insights. The ability to communicate complex findings effectively and influence stakeholders will be critical.

📌 Application Steps

To apply for this operations position:

• Submit your application through the provided link on Ashby.

• Tailor Your Resume: Highlight your 8+ years of quantitative UX research experience, focusing on roles in product/tech companies at scale. Emphasize specific skills like survey methodology, statistical analysis (Python/R, SQL), behavioral data analysis, and A/B testing. Quantify your achievements with metrics where possible.

• Curate Your Portfolio: Select 2-3 key projects that best showcase your ability to lead quantitative research, influence product strategy, and drive measurable impact. Ensure these examples highlight your technical depth, data storytelling, and any experience with AI/ML or advanced statistical methods.

• Prepare Your Narrative: Be ready to clearly articulate your experience, methodological approach, and the impact of your work during interviews. Practice summarizing your key projects and answering strategy-based questions.

• Research Good Maven: Understand their business (entertainment, fan-centric experiences, sports betting & gaming), their market position, and their commitment to data-driven decisions. This will help you 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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