User Researcher - Personalization

📍 Job Overview

Job Title: User Researcher - Personalization

Company: Spotify

Location: New York, NY

Job Type: Permanent

Category: User Experience Research / Product Research

Date Posted: February 23, 2026

Experience Level: Mid-Level (approx. 3+ years)

Remote Status: Remote OK (within North Americas, EST collaboration focus)

🚀 Role Summary

• Lead survey-driven and qualitative research initiatives to inform feature development, experimentation, and ongoing sentiment tracking for personalized and AI-driven audio experiences.

• Design, implement, and evolve scalable survey frameworks that support A/B testing, pre/post analysis, and continuous user perception measurement.

• Conduct qualitative research, including concept testing, usability studies, and interviews, to iteratively advise feature development and ensure intuitive, credible user experiences.

• Partner closely with cross-functional teams including Design, Product Management, Data Science, and Engineering to translate research insights into actionable product strategies.

• Leverage AI proficiency to thoughtfully integrate AI tools into research workflows and evaluate AI's impact within product experiences.

📝 Enhancement Note: This role is positioned within Spotify's Personalization Design team, focusing on highly scalable, data-informed user experiences. The emphasis on "AI proficiency" and "scalable research systems" suggests a need for researchers adept at building robust, repeatable methodologies that can support rapid iteration and continuous improvement in a data-rich environment. The role requires a strong quantitative foundation for experimentation and measurement, complemented by qualitative skills for deeper understanding.

📈 Primary Responsibilities

• Identify and prioritize critical research questions in close collaboration with Product Managers, Designers, Data Scientists, and Engineers.

• Design and execute comprehensive research plans, employing a mixed-methods approach with a strong emphasis on quantitative UXR methodologies such as survey design, experimentation, and perception measurement.

• Conduct qualitative research including concept testing, usability studies, semi-structured interviews, and diary studies to gain deep user insights.

• Translate complex qualitative findings into testable hypotheses and data-driven, measurable frameworks for product development.

• Develop and refine robust survey frameworks that enable efficient, scalable, and repeatable generation of user insights for ongoing product optimization.

• Synthesize and clearly communicate research findings and recommendations to diverse audiences, including leadership, ensuring research significantly influences product strategy and decision-making.

• Serve as a trusted research partner and subject matter expert for cross-functional collaborators, advocating for user needs throughout the product development lifecycle.

• Proactively identify opportunities to integrate AI tools and methodologies into research workflows to enhance rigor, efficiency, and impact.

📝 Enhancement Note: The emphasis on "identifying and prioritizing research questions" and "translating qualitative insights into testable hypotheses" highlights the strategic nature of this role. It's not just about executing research, but about proactively shaping the research agenda based on business objectives and user needs within the personalization domain. The requirement to "develop scalable survey frameworks" indicates a need for a researcher who can build repeatable systems rather than just conduct one-off studies.

🎓 Skills & Qualifications

Education:

Experience:

• 3+ years of applied user research experience, with a proven track record of leading and executing research projects from conception to completion.

Required Skills:

• Strong proficiency in quantitative user research methods, including survey design, sampling strategies, statistical analysis, and A/B test design and interpretation.

• Solid working knowledge of qualitative research methods such as usability testing, concept testing, semi-structured interviews, and diary studies.

• Ability to integrate quantitative data with qualitative insights to provide holistic and actionable recommendations.

• Experience in experimentation and A/B testing environments, understanding how to design for measurable outcomes.

• Skill in translating complex findings into clear, concise, and compelling communications for diverse stakeholders (e.g., product, design, engineering, leadership).

• Proven ability to work independently, manage multiple research projects simultaneously, and navigate ambiguity effectively.

Preferred Skills:

• Experience with sentiment analysis and perception measurement techniques.

• Familiarity with developing and managing large-scale survey programs or research systems.

• Experience in the audio streaming, music, or personalization technology space.

• Understanding of product development cycles and agile methodologies.

• Familiarity with data visualization tools for presenting research findings.

📝 Enhancement Note: The requirement for "AI proficiency" is a critical differentiator. Candidates should be prepared to discuss specific examples of how they have used AI in their research practice or how they approach evaluating AI-driven product features. The emphasis on "scalable research systems" suggests a preference for candidates who can think beyond individual studies and build frameworks for ongoing insight generation.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Demonstrate a portfolio showcasing a range of research projects, with a clear emphasis on quantitative studies (survey design, experimentation) and their impact on product decisions.

• Include case studies that highlight your ability to design and implement scalable research frameworks, particularly for continuous measurement or A/B testing support.

• Showcase examples of how you have translated qualitative insights into actionable hypotheses or measurable frameworks for product iteration.

• Provide evidence of your ability to collaborate effectively with cross-functional teams (Design, Product, Data Science, Engineering) throughout the research lifecycle.

Process Documentation:

• Prepare to discuss your systematic approach to research planning, including stakeholder alignment, question definition, methodology selection, and timeline management.

• Be ready to articulate your process for survey design, including question formulation, scale selection, sampling, and pre-testing strategies.

• Outline your methodology for analyzing and synthesizing both quantitative and qualitative data to derive actionable insights.

• Describe your process for communicating research findings, including tailoring your approach to different audiences and ensuring impact on decision-making.

📝 Enhancement Note: For this role, a portfolio should strongly emphasize quantitative research capabilities and the ability to build scalable systems. Candidates should be prepared to present case studies that demonstrate how their research directly informed product strategy, particularly in the context of personalization and AI-driven features. The ability to show iterative research processes and the impact of those iterations will be key.

💵 Compensation & Benefits

Salary Range:

• The United States base salary range for this position is $110,626 - $158,038 annually, plus equity.

• 📝 Enhancement Note: This range is considered competitive for a User Researcher with 3+ years of experience in a major tech hub like New York City. Factors influencing placement within the range will likely include depth of quantitative research expertise, specific experience with personalization/AI, and overall interview performance. Cost of living in New York City is high, making this range appropriate for the location.

Benefits:

• Health Insurance

• Six months of paid parental leave

• 401(k) retirement plan

• Monthly meal allowance

• 23 paid days off

• 13 paid flexible holidays

Working Hours:

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

• Collaboration within the Eastern Standard Time (EST) zone is expected.

• 📝 Enhancement Note: While a standard work week is implied, Spotify's "work from anywhere" philosophy may offer some flexibility in daily scheduling, provided core collaboration hours within EST are met.

🎯 Team & Company Context

🏢 Company Culture

Industry: Music Streaming & Audio Entertainment Technology

Company Size: Large (Spotify is a publicly traded company with over 10,000 employees globally).

Founded: 2006

Company Description: Spotify revolutionized music listening by providing on-demand access to millions of songs and podcasts. Their mission is to unlock the potential of human creativity by giving artists opportunities to live off their art and fans the chance to enjoy and be passionate about creators.

Team Structure:

• The Personalization Design team is a multidisciplinary group comprising designers, researchers, product managers, data scientists, and engineers.

• This role will report into a senior research lead or manager within the Personalization Design organization.

Methodology:

• Data-driven decision-making is paramount, with a strong emphasis on experimentation (A/B testing) and continuous measurement.

• User-centric design principles guide product development, with user research playing a critical role in informing strategy and execution.

• Iterative development cycles are common, requiring researchers to provide timely insights to support ongoing improvements.

• AI and machine learning are increasingly integrated into product features and user experiences.

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

📝 Enhancement Note: Spotify's culture is known for being innovative, data-driven, and collaborative. For an operations-focused role like this, expect a fast-paced environment that values measurable impact and cross-functional teamwork. The "work from anywhere" policy, with a collaboration focus on EST, suggests a blend of autonomy and structured interaction.

📈 Career & Growth Analysis

Operations Career Level: This role is positioned as a mid-level User Researcher. It requires independent execution of research projects and the ability to inform product strategy, but likely involves collaboration with more senior researchers on highly complex or strategic initiatives.

Reporting Structure: The User Researcher will likely report to a Lead User Researcher or Research Manager within the Personalization Design team. They will work closely with Product Managers, Designers, and Data Scientists on specific product initiatives.

Operations Impact: The User Researcher's work will directly influence the development and optimization of personalized audio experiences. This includes shaping how users discover new content, interact with AI-driven features, and perceive the overall Spotify platform. Their insights will drive user satisfaction, engagement, and retention, ultimately contributing to Spotify's business objectives.

Growth Opportunities:

• Skill Specialization: Deepen expertise in quantitative UXR, AI evaluation methodologies, or specific areas of personalization.

• Leadership Development: Transition into a Senior User Researcher role, taking on more complex projects, mentoring junior researchers, and contributing to research strategy.

• Cross-Functional Mobility: Potential to move into Product Management or UX Strategy roles by leveraging deep user understanding and strategic thinking.

• Learning & Development: Access to internal workshops, external conferences, and online courses to stay current with research methodologies and AI advancements.

📝 Enhancement Note: Spotify is a large organization with opportunities for vertical and horizontal growth. For a User Researcher, career progression typically involves moving from individual contributor to senior individual contributor, potentially leading research initiatives or mentoring. The emphasis on AI and personalization also opens doors to specialized roles within these emerging fields.

🌐 Work Environment

Office Type: Spotify offers a "work from anywhere" policy, with a primary collaboration focus within the Eastern Standard Time (EST) zone. While not tied to a specific office, this implies a need for strong remote collaboration tools and practices.

Office Location(s): While the role is remote within North America, Spotify has offices in major cities including New York, Boston, Los Angeles, and San Francisco.

Workspace Context:

• The environment is highly collaborative, requiring active participation in virtual meetings and asynchronous communication.

• Researchers will have access to a suite of digital tools for collaboration, data analysis, and communication.

• Expect to work within a fast-paced, agile development cycle where research insights are needed quickly to inform decisions.

• The focus is on delivering impactful research that drives product innovation.

Work Schedule: While a standard 40-hour work week is implied, Spotify's remote-first culture often allows for flexibility in daily scheduling, provided core collaboration hours within the EST timezone are met. This flexibility can be beneficial for managing complex research processes and data analysis.

📝 Enhancement Note: The "work from anywhere" model requires strong self-discipline and communication skills. Candidates should be comfortable working independently while actively engaging with remote teams. The EST collaboration focus is important for team synchronization.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter will review your application and assess alignment with the core requirements.

• Hiring Manager Interview: A conversation with the hiring manager to discuss your experience, research philosophy, and fit with the team.

• Portfolio Review & Presentation: A dedicated session where you will present detailed case studies from your portfolio, focusing on your research process, methodologies, insights, and impact. Expect to discuss your quantitative research skills, AI proficiency, and experience with personalization.

• Cross-Functional Interviews: Meetings with potential collaborators (e.g., Product Manager, Designer, Data Scientist) to assess your collaboration style and ability to translate research into product action.

• Research Team Interview: A discussion with other researchers on the team to evaluate your research craft, problem-solving abilities, and cultural fit.

• Final Round: Potential interviews with senior leadership.

Portfolio Review Tips:

• Quant Focus: Prioritize case studies that showcase your strength in quantitative research (survey design, experimentation, statistical analysis) and measurable impact.

• AI Integration: Clearly articulate how you've integrated AI into your research or evaluated AI-driven features.

• Scalability: Highlight projects where you designed or implemented scalable research systems or frameworks.

• Storytelling: Structure your case studies to tell a clear story: the problem, your approach, your insights, and the resulting product impact. Use data visualization effectively.

• Process Clarity: Be prepared to walk through your research process step-by-step, explaining your rationale for methodological choices.

• Deliverables: Show examples of your deliverables (e.g., survey reports, experimental results summaries, qualitative insights reports).

Challenge Preparation:

• Expect a potential take-home assignment or a live exercise focused on a research problem relevant to personalization or AI.

• Prepare to discuss how you would approach a research challenge with limited time or resources.

• Practice articulating your research strategy and methodology clearly and concisely.

• Be ready to answer questions about how you handle ambiguity and unexpected research outcomes.

📝 Enhancement Note: The portfolio review is critical for this role. Candidates should select examples that best demonstrate their quantitative UXR skills, experience with AI, and ability to build scalable research systems. Be prepared to go deep into the methodology and the impact of your work.

🛠 Tools & Technology Stack

Primary Tools:

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

• Experimentation Platforms: Familiarity with A/B testing frameworks and platforms (e.g., internal Spotify tools, Optimizely, VWO).

• Qualitative Research Tools: Tools for remote usability testing (e.g., UserTesting.com, Lookback), video conferencing (e.g., Zoom, Google Meet), and note-taking.

• AI & Machine Learning Tools: While not expected to be an AI developer, familiarity with AI concepts and tools for research analysis or evaluation is beneficial.

Analytics & Reporting:

• Statistical Software: Proficiency in statistical analysis tools or libraries (e.g., R, Python with libraries like Pandas, NumPy, SciPy, SPSS, SAS).

• Data Visualization Tools: Experience with tools like Tableau, Looker, or similar for presenting data trends and insights.

• Spreadsheet Software: Advanced skills in Excel or Google Sheets for data manipulation and analysis.

Collaboration & Project Management:

• Communication Platforms: Slack, Microsoft Teams.

• Project Management Tools: Jira, Asana, Trello, or similar for tracking research projects.

• Documentation Tools: Confluence, Google Workspace, Notion for documenting research plans, findings, and processes.

📝 Enhancement Note: While specific tools may vary, a strong foundation in survey design and analysis platforms, experimentation principles, and statistical analysis is essential. Proficiency in translating data into clear visualizations for reporting is also key.

👥 Team Culture & Values

Operations Values:

• Data-Driven: Decisions are grounded in rigorous data analysis and user insights.

• User-Centric: A deep understanding and advocacy for the user’s needs and experience.

• Collaborative: Strong emphasis on teamwork and cross-functional partnerships to achieve common goals.

• Innovative: Encouraging new ideas and approaches, especially in the realm of AI and personalization.

• Impact-Oriented: Focus on delivering tangible results and driving measurable improvements in user experience and business metrics.

• Curiosity & Learning: A commitment to continuous learning, staying abreast of research trends, and exploring new methodologies.

Collaboration Style:

• Highly collaborative, with researchers working as embedded partners within product teams.

• Open communication channels are encouraged, with regular feedback loops between research, design, product, and engineering.

• Emphasis on sharing knowledge and best practices across the research team.

• A proactive approach to problem-solving and a willingness to adapt methodologies based on team needs and project constraints.

📝 Enhancement Note: Spotify values a culture of curiosity, collaboration, and ownership. For a User Researcher, this means being an active participant in team discussions, proactively sharing insights, and being open to feedback from diverse perspectives.

⚡ Challenges & Growth Opportunities

Challenges:

• Balancing Speed and Rigor: The fast-paced nature of product development requires delivering timely insights without compromising research quality.

• Defining and Measuring Personalization: Quantifying the effectiveness of personalization features and AI-driven experiences can be complex.

• Navigating Ambiguity: Working on cutting-edge AI and personalization features often involves exploring uncharted territory with unclear user needs or technical constraints.

• Scaling Research Systems: Developing and maintaining survey frameworks and research processes that can support a large and dynamic product portfolio.

• AI Integration Nuances: Thoughtfully integrating AI into research workflows while maintaining ethical standards and ensuring methodological rigor.

Learning & Development Opportunities:

• AI Research Specialization: Opportunities to deepen understanding and application of AI in user research, including ethical considerations and evaluation frameworks.

• Advanced Quantitative Methods: Further training in statistical modeling, experimental design, and causal inference.

• Cross-Functional Exposure: Gaining deeper insights into product management, data science, and engineering processes.

• Industry Conferences & Publications: Support for attending leading UX research and AI conferences, and potentially contributing to industry knowledge.

• Mentorship: Access to senior researchers and leaders for career guidance and skill development.

📝 Enhancement Note: The challenges in this role are directly tied to the cutting-edge nature of AI and personalization. Success will require adaptability, strong analytical skills, and a proactive approach to learning and problem-solving.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you designed and implemented a scalable survey framework. What was the impact?" (Focus on process, metrics, and outcomes.)

• "How would you approach evaluating the user perception and credibility of an AI-generated playlist recommendation?" (Demonstrate AI evaluation skills and quantitative/qualitative approach.)

• "Walk us through an experiment you designed to test a personalization feature. What were your hypotheses, methodology, and key findings?" (Highlight experimental design and data interpretation.)

• "How do you translate qualitative insights into measurable hypotheses for A/B testing?" (Showcase bridging qualitative and quantitative research.)

Company & Culture Questions:

• "What excites you about personalization at Spotify, and how do you see AI playing a role?" (Show understanding of Spotify's product and your passion.)

• "How do you collaborate with Product Managers and Designers to ensure research findings are actionable?" (Assess cross-functional collaboration skills.)

• "How do you balance the need for rigorous research with the demands of a fast-paced product development cycle?" (Evaluate your adaptability and prioritization.)

Portfolio Presentation Strategy:

• Select High-Impact Quant Studies: Choose 2-3 case studies that strongly showcase your quantitative UXR skills, survey design expertise, and experience with experimentation.

• Highlight AI/Personalization: If possible, include a project related to personalization or AI evaluation.

• Structure Clearly: For each case study, present:

  1. The Challenge/Problem: What was the business or user question?
  2. Your Role & Approach: What was your specific contribution? What methodologies did you use and why?
  3. The Process: Detail your survey design, experimental setup, or qualitative data collection.
  4. The Insights: What did you discover?
  5. The Impact: How did your research influence product decisions, and what were the measurable outcomes?

• Quantify Everything: Use data, metrics, and clear visualizations to support your findings and demonstrate impact.

• Be Prepared for Deep Dives: Anticipate detailed questions about your methodology, analysis, and decision-making process.

📝 Enhancement Note: The interview process will heavily scrutinize your quantitative research skills, your ability to build scalable systems, and your comfort with AI. Be ready to defend your methodological choices and articulate the business impact of your research.

📌 Application Steps

To apply for this User Researcher position at Spotify:

• Submit your application through the provided link on jobs.lever.co.

• Tailor your Resume: Highlight keywords related to User Research, Personalization, Survey Design, Quantitative Research, Experimentation, A/B Testing, AI Proficiency, and cross-functional collaboration. Quantify your achievements wherever possible.

• Craft a Compelling Portfolio: Prepare a digital portfolio that showcases 2-3 strong case studies emphasizing your quantitative research expertise, experience with personalization/AI, and ability to build scalable research systems. Ensure clear articulation of process, insights, and impact.

• Prepare for the Portfolio Presentation: Practice presenting your case studies, focusing on clear storytelling, data visualization, and detailed explanations of your methodology and its impact. Be ready to answer in-depth questions.

• Research Spotify: Understand Spotify's product offerings, its mission, and recent developments in personalization and AI. Prepare thoughtful questions about the team and the role.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions based on the provided data and general industry knowledge. All details, especially regarding specific interview processes and team dynamics, should be verified directly with Spotify during the application and interview stages.