Senior UX Researcher

📍 Job Overview

Job Title: Senior UX Researcher
Company: Microsoft
Location: Redmond, Washington, United States
Job Type: Full-Time
Category: User Experience Research / Product Development
Date Posted: October 15, 2025
Experience Level: Mid-Senior Level (5-10 years)
Remote Status: Hybrid (4 days/week onsite)

🚀 Role Summary

• Lead and execute comprehensive user experience research initiatives for next-generation AI-powered monetization products, driving user-centered design and product strategy.
• Conduct a full spectrum of research methodologies, including exploratory, generative, and evaluative studies, to uncover user needs, pain points, and opportunities within the advertising and monetization landscape.
• Analyze quantitative and qualitative data from mixed methods research to provide actionable insights and evidence-based recommendations that directly influence product development and roadmap decisions.
• Collaborate closely with cross-functional teams, including product managers, designers, engineers, and AI specialists, to translate research findings into impactful product improvements and innovative solutions.
• Champion a user-first approach, ensuring that customer needs, goals, and aspirations are consistently prioritized throughout the entire product lifecycle, from ideation to launch and iteration.

📝 Enhancement Note: This role is positioned within Microsoft AI Monetization, a division focused on leveraging AI for advertising and monetization products. The Senior UX Researcher will be instrumental in shaping user experiences for advertisers, publishers, sellers, and consumers, requiring a strong understanding of user needs within complex business ecosystems and a commitment to data-driven decision-making.

📈 Primary Responsibilities

• Design and implement robust research plans using mixed methods (qualitative and quantitative) to address critical product questions and user needs.
• Conduct in-depth user interviews, usability testing, surveys, contextual inquiries, and other qualitative research methods to gather rich user insights.
• Analyze large datasets, including behavioral data, usage metrics, and survey responses, to identify trends, patterns, and opportunities for product enhancement.
• Translate complex research findings into clear, concise, and compelling narratives and presentations for diverse stakeholders, including executive leadership.
• Partner with product management and design teams to define research objectives, identify key hypotheses, and ensure research directly informs product strategy and design decisions.
• Rapidly evaluate early-stage prototypes and concepts to provide timely feedback and iterate on product designs before significant development investment.
• Contribute to the strategic vision for user research within the AI Monetization team, identifying new research methods and tools to enhance team capabilities.
• Advocate for users throughout the product development process, ensuring their needs and perspectives are represented in all decision-making.
• Stay abreast of the latest trends in AI, monetization, advertising technology, and UX research methodologies to bring innovative approaches to the team.
• Foster a collaborative research environment, sharing insights and best practices with other researchers and cross-functional team members.

📝 Enhancement Note: The emphasis on "AI-powered experiences focused on Monetization" and the need to move between "exploratory, generative research to rapid evaluations of prototyped ideas" suggests a dynamic research environment requiring adaptability and a proactive approach to uncovering user needs in evolving AI-driven product landscapes.

🎓 Skills & Qualifications

Education:

• Bachelor's or Master's degree in Human-Computer Interaction (HCI), Psychology, Sociology, Anthropology, Computer Science, or a related field, or equivalent practical experience.

Experience:

• 5-10 years of professional experience in UX research, with a proven track record of conducting impactful research for complex software products, preferably in B2B or SaaS environments.
• Demonstrated experience in designing and executing mixed-methods research studies, from generative exploration to evaluative testing.
• Experience working with AI-driven products or platforms is highly desirable.

Required Skills:

• Expertise in a wide range of qualitative research methods, including in-depth interviews, usability testing, ethnographic studies, and focus groups.
• Strong proficiency in quantitative research methods, including survey design, statistical analysis, and A/B testing interpretation.
• Advanced data analysis skills, with the ability to synthesize complex qualitative and quantitative data into actionable insights.
• Excellent communication, presentation, and storytelling skills, with the ability to articulate research findings and their implications to technical and non-technical audiences.
• Proven ability to collaborate effectively with cross-functional teams (Product Management, Design, Engineering, Marketing) and influence product strategy.
• Experience with prototyping tools and methods for rapid evaluation of user interfaces and concepts.
• Strong understanding of user-centered design principles and product development lifecycles.
• Ability to work independently, manage multiple projects simultaneously, and thrive in a fast-paced, agile environment.
• Demonstrated ability to uncover unspoken questions and address them with precision and detail.

Preferred Skills:

• Experience in the advertising technology (AdTech) or monetization space.
• Familiarity with AI/Machine Learning concepts and their application in user-facing products.
• Experience with large-scale data analysis tools and techniques.
• Knowledge of statistical software packages (e.g., R, SPSS) or data visualization tools.
• Experience mentoring junior researchers or leading research initiatives.

📝 Enhancement Note: The experience level of 5-10 years suggests this role requires a seasoned researcher capable of independent leadership and strategic contribution, not just execution. The emphasis on "uncovering the unspoken questions" points towards a need for critical thinking and deep analytical skills beyond standard research practices.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• A curated portfolio showcasing a diverse range of UX research projects, demonstrating a strong command of mixed-methods research.
• Case studies that clearly articulate the research problem, methodology, key findings, and the impact of your research on product decisions and outcomes.
• Examples of how you have translated complex user insights into actionable recommendations and influenced product roadmaps.
• Demonstrations of your ability to work with and analyze both qualitative and quantitative data, showcasing your analytical rigor.
• Evidence of your collaboration with cross-functional teams and your ability to communicate research effectively to various stakeholders.

Process Documentation:

• Examples of well-defined research plans, outlining objectives, methodologies, participant recruitment strategies, and timelines.
• Documentation showcasing your approach to synthesizing research findings into clear, compelling reports and presentations.
• Evidence of your ability to iterate designs based on research feedback and document the impact of those iterations.
• Proof of contribution to process improvements within research practices or product development workflows.

📝 Enhancement Note: Given the role's focus on AI-powered products and monetization, the portfolio should ideally include examples that touch upon understanding user behavior in complex digital ecosystems, evaluating new technologies, or informing strategy in revenue-generating product areas.

💵 Compensation & Benefits

Salary Range:

• Based on industry benchmarks for Senior UX Researchers in the Redmond, Washington area with 5-10 years of experience, the estimated salary range is approximately $130,000 - $180,000 annually. This estimation accounts for the high cost of living in the Seattle metropolitan area and Microsoft's competitive compensation structure for senior technical roles.

Benefits:

• Comprehensive health, dental, and vision insurance plans.
• Generous paid time off (PTO), holidays, and sick leave.
• Retirement savings plan (e.g., 401(k)) with company match.
• Stock options or restricted stock units (RSUs).
• Professional development opportunities, including training, conferences, and certifications.
• Employee assistance program (EAP).
• Parental leave and family support benefits.
• Access to Microsoft's extensive internal learning resources and employee discounts.
• Hybrid work flexibility, allowing for a balance between onsite collaboration and remote work.

Working Hours:

• Standard full-time work hours are typically 40 hours per week. Given the hybrid nature and the demands of a senior role, some flexibility may be expected to meet project deadlines and collaborate effectively with global teams. The role requires 4 days per week onsite in Redmond, WA.

📝 Enhancement Note: The salary range is an estimate based on publicly available data for similar roles at major tech companies in the Seattle area. Actual compensation may vary based on individual experience, performance, and specific team budgets. Microsoft is known for its robust benefits package, which typically includes stock options, comprehensive health coverage, and strong retirement plans.

🎯 Team & Company Context

🏢 Company Culture

Industry: Technology (Software, AI, Cloud Computing, Digital Advertising)
Company Size: Enterprise (Over 100,000 employees globally)
Founded: 1975

Team Structure:

• The Design, Research & Content team within Microsoft AI Monetization is described as a "friendly, diverse and fast-moving creative community."
• This team collaborates closely with Product Managers, Engineers, and AI Specialists to deliver holistic experiences.
• The reporting structure likely places the Senior UX Researcher within a research or design group, with direct influence on product teams.
• Cross-functional collaboration is a cornerstone, emphasizing teamwork and mutual support.

Methodology:

• User-Centered Design: A fundamental principle, ensuring all decisions are rooted in research and evidence.
• Data-Driven Decision Making: Emphasis on using research signals and experience to guide product direction, with a focus on long-term sustainable value over short-term KPIs.
• Agile Development: Implied by the "ship regularly" statement, suggesting iterative development cycles and rapid feedback loops.
• Holistic Experience Creation: Aiming to deliver comprehensive and cohesive user journeys across products.
• Innovation & Quality: A commitment to "breaking new ground" and delivering "category-defining products" with high standards.

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

📝 Enhancement Note: Microsoft's culture emphasizes a "growth mindset," innovation, and collaboration. The AI Monetization team specifically aims to blend user understanding with business acumen to shape the future of advertising in the AI era, highlighting a strategic and impactful operational focus.

📈 Career & Growth Analysis

Operations Career Level: Senior UX Researcher

• This level signifies a researcher who can independently lead complex research projects, mentor others, and contribute strategically to product direction. They are expected to handle ambiguity, drive initiatives, and have a significant impact on product outcomes.

Reporting Structure:

• The Senior UX Researcher will likely report to a Research Manager or Director within the Microsoft AI Monetization division. They will work closely with Product Managers and Designers on specific product teams, acting as a key research partner.

Operations Impact:

• The role has a direct and tangible impact on product success by ensuring that AI-powered monetization products meet user needs, are intuitive to use, and drive desired business outcomes for advertisers, publishers, and consumers. Research insights will shape the user experience, feature prioritization, and overall strategy of these critical revenue-generating products.

Growth Opportunities:

• Leadership Development: Opportunities to lead larger research initiatives, mentor junior researchers, and potentially move into management roles within UX Research.
• Specialization: Deepen expertise in AI-driven product research, monetization strategies, or specific user segments (e.g., enterprise advertisers).
• Cross-Functional Mobility: Potential to move into related roles such as Product Management, Design Strategy, or Program Management within Microsoft.
• Skill Enhancement: Continuous learning through internal training, access to research conferences, and exposure to cutting-edge AI technologies and research methodologies.
• Impactful Projects: Opportunity to work on high-visibility products with global reach, contributing to Microsoft's mission and shaping the future of AI in monetization.

📝 Enhancement Note: The "Senior" title implies a trajectory towards leadership, strategic influence, and mentorship. The role is critical in a division focused on revenue generation through AI, offering significant visibility and impact for the chosen candidate.

🌐 Work Environment

Office Type: Hybrid Work Model, with a strong emphasis on in-office collaboration.
Office Location(s): Redmond, Washington, United States (Primary location for this role). The description also mentions Mountain View, CA as a potential alternative, but Redmond is specified for this particular opening.

Workspace Context:

• Collaborative Environment: The team fosters a supportive and collaborative atmosphere, encouraging mutual support and knowledge sharing. The hybrid model requires 4 days per week onsite, indicating a preference for in-person interaction for brainstorming, ideation, and team cohesion.
• Tools & Technology: Researchers will have access to Microsoft's extensive internal tools, platforms, and cutting-edge AI technologies, enabling them to conduct sophisticated research.
• Team Interaction: Opportunities for frequent interaction with product managers, designers, engineers, and fellow researchers, facilitating a rich exchange of ideas and perspectives.

Work Schedule:

• Primarily standard business hours (40 hours/week), with potential for flexibility to accommodate project needs and global team collaboration. The requirement for 4 days onsite in Redmond highlights the importance of in-person collaboration within the team's workflow.

📝 Enhancement Note: The 4-day onsite requirement for a hybrid role suggests a deliberate strategy to maximize in-person collaboration, team building, and spontaneous ideation within the Redmond office. This environment is designed to foster innovation and strong working relationships.

📄 Application & Portfolio Review Process

Interview Process:

• Screening Call: Initial conversation with a recruiter to assess basic qualifications, experience, and cultural fit.
• Hiring Manager Interview: In-depth discussion about your experience, research philosophy, and approach to problem-solving. This may involve behavioral questions.
• Portfolio Review & Presentation: A key stage where you'll present 1-2 of your strongest research case studies, detailing your process, findings, and impact. This is often followed by a Q&A.
• Technical/Skills Assessment: This could involve a research challenge or a deep dive into your data analysis capabilities, potentially with a specific scenario related to AI monetization.
• Team/Cross-Functional Interviews: Meetings with potential peers (other researchers, designers) and cross-functional partners (Product Managers, Engineers) to assess collaboration style and ability to integrate into the team.
• Final Interview: Often with a senior leader, focusing on strategic thinking, leadership potential, and overall fit with Microsoft's values.

Portfolio Review Tips:

• Select Impactful Projects: Choose 2-3 projects that best showcase your mixed-methods expertise, problem-solving skills, and tangible impact on product development. Prioritize projects relevant to AI, monetization, or complex B2B/SaaS products if possible.
• Structure Your Narrative: For each project, clearly articulate: the business/product problem, your research objectives, your chosen methodology (and why), key findings, the actionable insights you derived, and the resulting product changes/impact. Quantify impact where possible (e.g., "led to a X% increase in conversion," "reduced user errors by Y%").
• Highlight Collaboration: Demonstrate how you worked with cross-functional partners, incorporated their feedback, and influenced their decisions.
• Showcase Data Analysis: Provide examples of how you analyzed both qualitative and quantitative data, and how these analyses informed your conclusions.
• Be Prepared for Deep Dives: Anticipate detailed questions about your methodology, decision-making process, and how you handled challenges or unexpected findings.
• Tailor to Microsoft: Understand Microsoft's values (growth mindset, customer focus, quality, simplicity) and try to weave them into your presentation.

Challenge Preparation:

• Anticipate Research Scenarios: Be ready for hypothetical research challenges related to designing AI features, understanding user adoption of new technologies, or optimizing monetization strategies.
• Outline Your Approach: Practice articulating a structured research plan for a given problem, including defining objectives, selecting methods, planning for data analysis, and outlining communication strategies.
• Think About Trade-offs: Consider the constraints (time, resources, data availability) and how you would make trade-offs in your research approach.
• Focus on Actionability: Demonstrate how your research would lead to concrete, actionable recommendations for product teams.

📝 Enhancement Note: The portfolio review is a critical gate. Candidates should prepare to not just present their work, but to defend their methodological choices and articulate the business value and user impact of their research. The emphasis on AI and monetization means demonstrating an understanding of these complex domains will be advantageous.

🛠 Tools & Technology Stack

Primary Tools:

• User Research Platforms: Tools for managing studies, participant recruitment, and data collection (e.g., UserTesting.com, Qualtrics, Maze, UserZoom).
• Collaboration Suites: Microsoft Teams, SharePoint, OneDrive for seamless team communication and document sharing.
• Prototyping & Design Tools: Familiarity with tools like Figma, Sketch, Adobe XD, or Microsoft's own design tools for understanding and evaluating prototypes.

Analytics & Reporting:

• Data Analysis Software: Proficiency in tools for qualitative data analysis (e.g., Dovetail, NVivo) and quantitative analysis (e.g., Excel, R, SPSS, Python libraries like Pandas).
• BI & Visualization Tools: Experience with tools like Power BI, Tableau, or similar for creating dashboards and visualizing research data.
• Product Analytics Platforms: Familiarity with tools like Google Analytics, Adobe Analytics, or internal Microsoft telemetry tools for understanding user behavior.

CRM & Automation:

• While not a core CRM role, understanding how user data is managed and potentially linked to customer profiles within CRM systems (like Microsoft Dynamics 365) can be beneficial.
• Familiarity with workflow automation concepts within product development or research operations.

📝 Enhancement Note: Given Microsoft's internal ecosystem, proficiency with Microsoft-specific tools like Teams, Power BI, and potentially Dynamics 365 is a significant advantage. The role requires comfort with both qualitative and quantitative data analysis tools.

👥 Team Culture & Values

Operations Values:

• Quality: A commitment to delivering "category-defining products" with high standards of usability, reliability, and design. This translates to rigorous research and a focus on delivering high-value insights.
• Simplicity: A drive to avoid overcomplication, making products intuitive and easy to use. Research should aim to uncover opportunities for simplification and clarity.
• Safety and Security: Non-negotiable principles that must be considered in all product development and user experience research.
• Evaluation: A culture that values thoughtful analysis of signals, a willingness to adapt based on data and experience, and a focus on long-term sustainable value.
• Kindness: A core organizational value emphasizing respect, support, and continuous learning among team members. This fosters a positive and inclusive work environment.
• Customer Focus: A deep dedication to understanding and serving the needs, problems, goals, and aspirations of users.

Collaboration Style:

• Cross-functional Integration: The team actively works across disciplines (Design, Research, Content, PM, Eng, AI) to create cohesive user experiences. Researchers are expected to be integrated partners, not isolated contributors.
• Evidence-Based Dialogue: Decisions are grounded in research and data, fostering productive discussions and debates based on evidence.
• Supportive Environment: Team members support each other, creating a space for learning, growth, and shared success.
• Growth Mindset: An openness to new ideas, continuous learning, and embracing challenges as opportunities for development.

📝 Enhancement Note: The explicit mention of "Kindness" and a "growth mindset" alongside core business values like "Quality" and "Evaluation" indicates a culture that balances high performance with employee well-being and continuous improvement.

⚡ Challenges & Growth Opportunities

Challenges:

• Complexity of AI Monetization: Navigating the intricate user needs and business models within AI-driven advertising and monetization products requires deep analytical skills and adaptability.
• Rapid Technological Evolution: Keeping pace with advancements in AI and its application to user experiences necessitates continuous learning and evolving research methodologies.
• Balancing User Needs with Business Goals: Effectively advocating for users while ensuring products meet critical business objectives and revenue targets.
• Translating Research into Action: Ensuring research insights are understood, adopted, and lead to tangible product improvements in a fast-paced environment.
• Hybrid Work Dynamics: Optimizing collaboration and team cohesion within a hybrid work model, ensuring consistent research impact regardless of location.

Learning & Development Opportunities:

• Specialized Training: Access to internal and external training on advanced UX research techniques, AI ethics, monetization strategies, and data analysis tools.
• Industry Conferences: Opportunities to attend leading UX research and AI conferences to stay at the forefront of the field.
• Mentorship Programs: Access to mentorship from senior researchers and leaders within Microsoft to guide career development.
• Internal Knowledge Sharing: Participating in research communities of practice, brown bags, and workshops to share and gain knowledge.
• Exposure to Cutting-Edge AI: Working directly with AI technologies and specialists provides unique learning opportunities in a rapidly growing field.

📝 Enhancement Note: This role offers significant opportunities to grow expertise in a highly strategic and rapidly evolving area of technology (AI in monetization), providing a strong foundation for future career advancement within the tech industry.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you had to conduct research in a rapidly evolving technological space like AI. What were the unique challenges and how did you address them?" (Focus on adaptability, methodology, and handling ambiguity.)
• "How would you approach understanding the unmet needs of advertisers using AI-powered tools for campaign optimization?" (Demonstrate your research planning process, user segmentation, and hypothesis generation.)
• "Walk me through a research project where your findings significantly influenced product strategy or led to a substantial improvement in user experience or business metrics. What was your role and what was the outcome?" (Prepare a compelling case study highlighting impact and your contribution.)
• "How do you balance the need for deep, exploratory research with the demand for rapid, evaluative feedback on prototypes in an agile environment?" (Showcase your understanding of different research phases and your ability to adapt methodologies.)

Company & Culture Questions:

• "What interests you about Microsoft's mission and specifically about working within AI Monetization?" (Align your interests with Microsoft's goals and the division's focus.)
• "How do you embody Microsoft's core values, such as 'Growth Mindset' and 'Kindness,' in your professional work and collaborations?" (Provide specific examples of how you demonstrate these values.)
• "Describe your experience working in a hybrid environment. How do you ensure effective collaboration and communication with your team?" (Address the 4-day onsite requirement and your approach to hybrid work.)
• "How do you ensure the quality and reliability of your research findings, especially when dealing with complex data or novel AI applications?" (Reference your commitment to rigorous methodology and evidence-based decision-making.)

Portfolio Presentation Strategy:

• Choose Your Best & Most Relevant: Select 1-2 projects that best highlight your mixed-methods skills, impact, and relevance to AI/monetization.
• Tell a Data-Informed Story: Structure your presentation around the narrative of the research process: Problem -> Research Questions -> Methodology -> Findings -> Insights -> Recommendations -> Impact.
• Quantify Impact: Wherever possible, use data and metrics to demonstrate the success of your research and the products it influenced.
• Be Ready for Q&A: Anticipate questions about your choices, challenges, alternative approaches, and the broader implications of your findings.
• Highlight Collaboration: Explicitly mention how you partnered with PMs, designers, and engineers to ensure your research was actionable and integrated.

Challenge Preparation:

• Deconstruct the Prompt: If given a research challenge, take a moment to understand the core problem, the target users, and the business context.
• Outline Your Approach: Verbally or visually outline your proposed research plan: objectives, target audience, key questions, chosen methods (and rationale), expected deliverables.
• Consider Constraints: Think about potential time, budget, and data limitations and how you'd adapt.
• Focus on Actionability: Emphasize how your proposed research would lead to concrete recommendations that the product team can act upon.

📝 Enhancement Note: Interviewers will be looking for a blend of strong research craft, strategic thinking, collaborative spirit, and a clear understanding of how research drives business outcomes, particularly in the context of AI and monetization.

📌 Application Steps

To apply for this Senior UX Researcher position:

• Submit your application through the Microsoft Careers portal via the provided URL.
• Craft a Targeted Resume: Tailor your resume to highlight your experience with mixed-methods research, AI/ML product exposure, data analysis, and successful collaboration with cross-functional teams. Use keywords from the job description.
• Prepare Your Portfolio: Curate 2-3 strong case studies that showcase your research process, methodologies, key findings, and demonstrable impact on product development. Ensure it's easily accessible (e.g., PDF or a dedicated website).
• Research Microsoft AI Monetization: Understand the division's goals, the types of products they develop, and the current landscape of AI in advertising and monetization. This will help you tailor your responses and demonstrate genuine interest.
• Practice Your Presentation: Rehearse your portfolio presentation, focusing on clear storytelling, articulating your research process, and highlighting the impact of your work. Be ready to answer in-depth questions about your methodology and decision-making.
• Prepare for Behavioral & Situational Questions: Reflect on your past experiences that demonstrate your skills in collaboration, problem-solving, handling ambiguity, and embodying Microsoft's core values.

⚠️ 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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