UX Researcher

📍 Job Overview

Job Title: Senior Mixed Methods Researcher

Company: Glance

Location: Bangalore, Karnataka, India

Job Type: Full-Time

Category: User Experience & Research Operations

Date Posted: 2026-06-24T11:53:14

Experience Level: 7+ Years (with at least 3 years in mixed methods)

Remote Status: On-site

🚀 Role Summary

• Lead strategic mixed-methods research programs to decode consumer behavior and inform product, growth, and data science strategies.

• Act as the senior research voice, bridging qualitative and quantitative insights for critical business questions.

• Drive the integration of AI into research craft, setting methodological standards and evaluating new tools.

• Mentor existing UX researchers in methodology, study design, and AI fluency.

• Partner closely with Product, Growth, and Data Science teams to translate research findings into actionable recommendations and testable hypotheses.

📝 Enhancement Note: While the role is titled "UX Researcher," the responsibilities, particularly around strategic research, mixed-methods leadership, AI integration, and mentoring, position this as a Senior Mixed Methods Researcher or Lead UX Researcher role within a dedicated behavioral insights unit. The focus on "decoding consumer behavior" and informing "strategy" elevates it beyond typical product-focused UX research. The emphasis on AI integration and setting methodological standards is a key differentiator.

📈 Primary Responsibilities

• Design and lead comprehensive mixed-methods research programs, encompassing consumer understanding, experimentation, and strategic inquiry, from initial problem framing through to final recommendation delivery.

• Conduct grounded theory-style strategic research to frame open-ended questions and develop evidence-based answers.

• Inform experiment design with principles of behavioral science and lead post-experiment analysis to uncover the underlying reasons for success or failure, and to guide future testing.

• Generate hypotheses for Data Science teams by identifying qualitative signals and investigating anomalies in product and funnel data to explain numerical trends.

• Collaborate closely with Product, Growth, and Data Science teams to analyze funnel behavior, decision heuristics, and cohort identification.

• Critically evaluate quantitative outputs, cross-checking data-driven narratives to ensure a holistic understanding.

• Mentor junior UX researchers on advanced methodology, study design, stakeholder engagement, and AI fluency.

• Establish and uphold the team's methodological standards for mixed-methods research, defining benchmarks for rigor and speed.

• Define and champion best practices for AI utilization in research, including evaluating tools, developing workflows, and teaching effective AI-augmented research techniques.

• Develop and author internal frameworks and playbooks to enhance the collective research capabilities of the team.

📝 Enhancement Note: The responsibilities clearly indicate a senior-level role focused on strategic impact and methodological leadership, with a strong emphasis on bridging qualitative and quantitative data and integrating AI. The scope includes not just executing research but also defining how research is done and how AI is leveraged.

🎓 Skills & Qualifications

Education: While not explicitly stated, a Bachelor's or Master's degree in a relevant field such as Psychology, Sociology, Anthropology, Human-Computer Interaction, Statistics, or a related discipline is typically expected for this level of role.

Experience:

• 7+ years of experience in user, consumer, or behavioral research.

• Minimum of 3 years leading studies that integrate both qualitative and quantitative methods.

• Demonstrated experience in cross-cultural research, including direct US fieldwork, prior US consumer research practice, or a proven track record of bridging geographic and cultural distances in research.

• Mentoring experience (formal or informal) with junior researchers. Required Skills:

• Mixed Methods Research: Expertise in designing and executing research that effectively combines qualitative and quantitative approaches.

• Behavioral Science: Strong grounding in decision heuristics, judgment under uncertainty, and application of at least one rigorous behavioral framework.

• Qualitative Research: Proficiency in methods such as strategic research, grounded theory, ethnography, diary studies, and deep qualitative interviewing.

• Quantitative Research: Ability to critically interpret quantitative data, inform experiment design, and analyze funnel metrics.

• AI Integration in Research: Demonstrated ability to use AI tools in research workflows, evaluate their effectiveness, and understand their limitations. Experience with prompt engineering or building AI-augmented research processes is highly valued.

• Hypothesis Generation: Skill in translating qualitative insights into testable hypotheses for quantitative analysis and experimentation.

• Stakeholder Engagement: Proven ability to effectively communicate research findings and recommendations to Product, Growth, and Data Science teams, ensuring adoption.

• Mentoring & Coaching: Experience guiding and developing junior researchers in their methodological and professional growth.

• Cross-Cultural Research: Ability to conduct research effectively across different cultural contexts, with a specific requirement for understanding US consumers.

• Product & Strategy Acumen: Track record of research recommendations influencing product roadmaps and strategic decisions.

• Curiosity & Learning Agility: A proactive, self-starting attitude with a habit of continuous learning across methods and disciplines.

Preferred Skills:

• Background in consumer tech, e-commerce, or content/discovery products.

• Experience with agentic commerce, conversational AI, or AI-driven shopping categories.

• Direct experience researching US consumers while based outside the US.

• Experience shaping strategic or leadership-level decisions, not just feature-level product execution.

• Close collaboration experience with Data Science or ML teams, including informing model evaluation or AI product assessment.

• Strong command of longitudinal qualitative methods (e.g., diary studies, ethnographic research, extended panel work).

• Public research output (e.g., published papers, conference talks, methodology contributions).

• Familiarity with common remote research tools such as dscout, Userlytics, Maze, Qualtrics, Lyssna, UXtweak, or equivalents.

📝 Enhancement Note: The requirements emphasize a blend of deep research expertise, strategic thinking, and practical application of AI. The "hustler's instinct" and "fast-learning habit" point to a need for proactive, adaptable individuals. The preference for specific product/category experience and public research output suggests a desire for candidates who are thought leaders or have a strong track record of innovation.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Mixed-Methods Case Studies: Showcase projects where you've successfully integrated qualitative and quantitative data to answer complex questions. Demonstrate the research design, methods used, key findings, and the impact of your recommendations.

• Strategic Impact Examples: Highlight instances where your research directly influenced product strategy, roadmap prioritization, or business decisions. Quantify the impact where possible (e.g., user adoption, conversion improvements, cost savings).

• AI Integration Showcase: Include examples of how you've used AI tools in your research process (e.g., for synthesis, analysis, hypothesis generation, prompt engineering). Explain the specific workflows, benefits, and any challenges encountered.

• Mentoring & Framework Development: If possible, include examples of frameworks, playbooks, or best practices you've developed or contributed to, demonstrating your ability to elevate team capabilities.

• Cross-Cultural Research Examples: Present research conducted with diverse user groups, particularly demonstrating understanding of US consumer behavior or bridging cultural/geographic divides.

Process Documentation:

• Research Program Design: Provide examples of how you frame research problems, define objectives, select appropriate methodologies (qualitative, quantitative, mixed-methods), and plan research timelines and resources for complex strategic initiatives.

• AI-Augmented Workflow Examples: Detail specific AI-driven workflows you've implemented for tasks like qualitative data synthesis, thematic analysis, persona generation, or hypothesis generation. Clearly articulate the "before" and "after" of using AI.

• Recommendation & Implementation Tracking: Demonstrate how you track the adoption and impact of your research recommendations, including how you partner with stakeholders to ensure insights lead to tangible outcomes.

📝 Enhancement Note: For a senior role with a focus on methodological leadership and AI integration, a portfolio is critical. It needs to go beyond showcasing individual studies to demonstrating strategic thinking, process improvement, and the ability to influence and mentor others. The emphasis on AI integration and cross-cultural work means these elements should be prominently featured.

💵 Compensation & Benefits

Salary Range: Based on industry benchmarks for Senior Mixed Methods Researchers with 7+ years of experience in Bangalore, India, the estimated annual salary range is ₹25,00,000 to ₹40,00,000. This range can vary based on the candidate's specific experience, skill set, and negotiation.

Benefits:

• Comprehensive health insurance (medical, dental, vision) for employees and their dependents.

• Generous paid time off (PTO), including vacation days, sick leave, and public holidays.

• Retirement savings plan/provident fund contributions.

• Professional development opportunities, including access to conferences, training, and online courses.

• Performance-based bonuses and potential for stock options or equity.

• Employee assistance programs (EAP) for mental and emotional well-being.

• Subsidized meals or meal allowances.

• Commuting assistance or on-site transportation.

• Opportunities for internal mobility and career advancement within the Glance/InMobi Group.

Working Hours: The standard working hours are approximately 40 hours per week, aligning with typical full-time employment in India. Given the role's senior nature and the team's focus on strategic impact, some flexibility may be expected to meet project deadlines or critical research needs. The team operates in-office in Bangalore.

📝 Enhancement Note: Salary estimation is based on Glassdoor, LinkedIn Salary, and industry reports for Senior UX Researchers/Behavioral Scientists in Bangalore, India, considering the specified experience level (7+ years) and the role's senior and strategic nature. Benefits are inferred from typical offerings for tech companies of Glance's scale and funding, especially those operating in India and targeting senior talent. The "on-site" work arrangement in Bangalore is noted.

🎯 Team & Company Context

🏢 Company Culture

Industry: Consumer Technology, AI Commerce, Digital Advertising, Mobile Platforms. Glance AI operates at the intersection of e-commerce, AI, and consumer technology, aiming to create inspiration-led shopping experiences.

Company Size: Glance is part of the InMobi Group, a global technology leader reaching over 2 billion devices and serving more than 30,000 enterprise brands worldwide. Glance itself has a significant user base across Android, iOS, and TV in the US and Asia, indicating a large and dynamic operational scale.

Founded: Glance AI is part of the InMobi Group, which was founded in 2007. Glance itself was launched later, focusing on screen-based discovery experiences. The company is backed by major investors including Google, Jio Platforms, and Mithril Capital, signifying strong financial backing and strategic partnerships.

Team Structure:

• The role is within the "Foresight & Behavioral Insights Unit."

• This unit spans consumer understanding, market intelligence, experimentation, and Voice of Consumer (VoC) programs.

• The team works closely with Product, Growth, Marketing, and Data Science.

• The Senior Mixed Methods Researcher will act as a senior research voice into Product, Growth, and Data Science, with mentoring responsibilities for existing UX researchers.

• The team operates in-office out of Bangalore. Methodology:

• Data-Driven Decision Making: Emphasis on using data and insights to shape strategy and product development.

• Behavioral Science Integration: Application of psychological principles to understand and predict consumer behavior.

• AI-Augmented Research: Daily use of AI as a research tool, with a focus on practical integration and critical evaluation.

• Mixed-Methods Approach: Combining qualitative and quantitative research to gain a holistic understanding.

• Grounded Theory & Exploratory Research: Conducting research where the problem and solution are not predefined.

• Experimentation & Iteration: Informing and interpreting A/B tests and other experiments to drive product improvements.

Company Website: Glance.com (or relevant InMobi Group sites)

📝 Enhancement Note: The company culture is characterized by innovation in AI and consumer tech, a focus on large-scale user engagement, and a strong emphasis on data-driven insights. The research team is positioned as a strategic partner, directly influencing product and business decisions, with a forward-thinking approach to leveraging AI. The "on-site" requirement in Bangalore is a key detail for candidates.

📈 Career & Growth Analysis

Operations Career Level: This is a Senior Individual Contributor (IC) role. It represents a significant step up from a standard UX Researcher position, focusing on strategic impact, methodological leadership, and mentorship rather than direct people management. It's a role for an experienced researcher who wants to deepen their craft, influence team practices, and drive high-impact initiatives.

Reporting Structure: The Senior Mixed Methods Researcher will report into a lead within the Foresight & Behavioral Insights Unit. They will work closely with Product, Growth, and Data Science teams, acting as a senior research resource for these departments. While not a people management role, it includes mentoring responsibilities for junior researchers on the team.

Operations Impact: The research conducted by this role directly influences the core product strategy, user experience, and growth initiatives of Glance AI. By decoding consumer behavior and integrating AI into research, the researcher's insights will shape how hundreds of millions of users interact with inspiration-led commerce and AI-powered experiences. The impact is significant, affecting product roadmaps, experiment design, and the overall strategic direction of the platform.

Growth Opportunities:

• Methodological Leadership: Opportunity to define and elevate the mixed-methods research practice and AI integration standards for the entire research team.

• Strategic Influence: Direct involvement in shaping high-level product and business strategy for a platform reaching hundreds of millions of users globally.

• Skill Specialization: Deepen expertise in behavioral science, AI in research, and cross-cultural consumer insights.

• Mentorship & Coaching: Develop leadership and coaching skills by mentoring junior researchers.

• Career Progression: Potential pathways to Lead Researcher, Principal Researcher, or specialized roles focusing on AI product research or strategic insights within Glance or the broader InMobi Group.

• Industry Recognition: Opportunities to contribute to public research output (papers, talks) if desired.

📝 Enhancement Note: This role offers a significant opportunity for experienced researchers to shape a function and influence strategy at a large scale, with a unique focus on AI integration. The growth path emphasizes deep expertise and influence rather than traditional management hierarchies.

🌐 Work Environment

Office Type: The role is explicitly stated as "in-office" in Bangalore. This suggests a traditional office environment designed for collaboration, team interaction, and focused work. The company culture likely fosters a blend of independent work and team-based problem-solving.

Office Location(s): Bangalore, Karnataka, India. This implies working within a major tech hub in India. Specific office details (e.g., amenities, accessibility) would need to be confirmed directly.

Workspace Context:

• Collaborative Environment: Working closely with Product, Growth, and Data Science teams will require strong communication and collaboration skills, likely facilitated through team meetings, workshops, and shared workspaces.

• Tools & Technology: Access to standard research tools, data analysis platforms, and potentially AI research platforms and tools will be provided. The role requires fluency in leveraging these technologies effectively.

• Team Interaction: As a senior member and mentor, the researcher will have opportunities to interact with and guide junior researchers, fostering a supportive and knowledge-sharing environment. The emphasis on bridging geographic and cultural distances implies a need for strong remote collaboration skills within the team, even if the role itself is on-site.

Work Schedule: The standard working hours are approximately 40 hours per week, typical for a full-time role. However, as a senior individual contributor driving strategic initiatives, there may be an expectation of flexibility to meet project demands and ensure timely delivery of critical insights. The on-site nature suggests a structured work week within the Bangalore office.

📝 Enhancement Note: The "on-site" requirement in Bangalore is a critical factor. Candidates should expect a collaborative office-based environment where they will interact with various cross-functional teams. The work environment likely supports deep focus work while encouraging frequent collaboration.

📄 Application & Portfolio Review Process

Interview Process: Expect a multi-stage interview process designed to assess research expertise, strategic thinking, AI fluency, and cultural fit.

1. Initial Screening (Recruiter/Hiring Manager): A preliminary call to discuss background, experience, alignment with the role's core requirements, and AI experience.

2. Technical/Methodology Interview (Senior Researcher/Team Lead): Deep dive into your research methodologies (mixed-methods, qualitative, quantitative), behavioral science application, and experience in cross-cultural research. Expect discussions on study design, data analysis, and interpretation.

3. AI & Strategic Thinking Interview (Hiring Manager/Senior Stakeholder): Focus on your practical AI integration in research, your ability to frame strategic questions, generate hypotheses, and translate insights into actionable recommendations. This may include hypothetical problem-solving scenarios.

4. Case Study Presentation/Portfolio Review: You will likely be asked to present one or two key projects from your portfolio, demonstrating your mixed-methods expertise, strategic impact, and AI usage. This is a crucial stage for showcasing your craft.

5. Cross-Functional Stakeholder Interviews: Meetings with representatives from Product, Growth, or Data Science to assess collaboration style, communication skills, and ability to influence.

6. Final Round (Senior Leadership): A discussion with senior leadership to assess overall fit, strategic vision, and potential for long-term contribution.

Portfolio Review Tips:

• Curate Strategically: Select 2-3 of your most impactful projects that best showcase your mixed-methods expertise, strategic influence, and AI integration.

Tailor your selection to highlight skills most relevant to the job description.

• Structure Your Narrative: For each case study, clearly articulate:

  • The Problem: What was the strategic or product challenge?
  • Your Approach: How did you design and execute the mixed-methods research? Specifically detail the qualitative and quantitative components and how they were integrated.
  • AI Integration: Where and how did you leverage AI tools? What were the tangible benefits or challenges?
  • Key Insights: What were the most critical findings?
  • Impact & Recommendations: What recommendations did you make, and what was the resulting impact on the product, strategy, or business? Quantify if possible.

• Demonstrate AI Fluency: Be prepared to discuss specific AI tools used, workflows built or adopted, and your critical judgment regarding AI outputs. Be ready to share examples of where AI was right, wrong, or enhanced your work.

• Highlight Mentorship: If you have formal or informal mentoring experience, weave it into your narrative or have specific examples ready.

• Practice Your Presentation: Rehearse your case studies to ensure a clear, concise, and compelling presentation within the allotted time. Be ready to answer in-depth questions about your process and decisions.

Challenge Preparation:

• AI & Research Scenarios: Be ready to discuss how you would approach a research problem using AI, or how you would critically evaluate AI-generated insights.

• Methodological Dilemmas: Prepare to discuss trade-offs between different research methods, how you'd handle ambiguity in research questions, or how you'd integrate new methods.

• Stakeholder Management: Practice articulating complex research findings and recommendations in a way that resonates with non-research audiences (Product Managers, Data Scientists).

📝 Enhancement Note: The interview process and portfolio review are designed to test not just research skills but also strategic thinking, AI proficiency, and the ability to mentor and influence. Candidates should prepare to articulate their process, impact, and AI usage with concrete examples.

🛠 Tools & Technology Stack

Primary Tools (Likely Used or Expected Familiarity):

• Qualitative Research Platforms: dscout, Userlytics, UserTesting.com, Lookback, Maze, Qualtrics (for surveys and qualitative feedback collection).

• Quantitative Research & Analytics: Qualtrics, SurveyMonkey, Google Analytics, Amplitude, Mixpanel, SQL for data extraction and analysis.

• Collaboration & Documentation: Google Workspace (Docs, Sheets, Slides), Confluence, Jira, Miro/FigJam for workshops and synthesis.

• AI Research Tools: Various LLM platforms (e.g., ChatGPT, Claude, Gemini), AI-powered synthesis tools, prompt engineering environments. The company is actively integrating AI, so familiarity with emerging AI research tools is a plus.

Analytics & Reporting:

• Data Visualization: Tableau, Power BI, Looker, or internal dashboarding tools.

• Statistical Software (Optional but beneficial): R, Python (for advanced analysis).

CRM & Automation: While not directly managing CRM, understanding how user data flows from CRM and other systems into research analysis is valuable. Familiarity with how research insights feed into growth automation strategies is also a plus.

📝 Enhancement Note: The job description explicitly mentions familiarity with dscout, Userlytics, Maze, Qualtrics, Lyssna, and UXtweak as preferred. The emphasis on AI integration suggests a need for adaptability and willingness to explore new AI-powered research tools. Proficiency in data analysis and visualization will be crucial for bridging qualitative and quantitative findings.

👥 Team Culture & Values

Operations Values:

• Curiosity & Insight-Driven: A deep-seated desire to understand consumer behavior and translate that understanding into actionable insights that drive business value.

• Methodological Rigor & Innovation: Commitment to robust research practices while also embracing new methodologies, especially AI-driven approaches, to push the boundaries of what's possible.

• Collaboration & Partnership: Working effectively with cross-functional teams (Product, Growth, Data Science) to ensure research is integrated and influential.

• Impact & Adoption: Focusing on research that leads to tangible outcomes and ensuring recommendations are adopted by stakeholders.

• Continuous Learning: A habit of reading widely, experimenting with new tools and methods, and staying ahead of industry trends, particularly in AI and behavioral science.

Collaboration Style:

• Proactive & Influential: The team aims to be a strategic partner, not just a service provider. This involves proactively identifying research opportunities and influencing strategic direction.

• Bridging Disciplines: Strong emphasis on connecting qualitative signals with quantitative data, and on translating insights for diverse audiences (e.g., Data Scientists, Product Managers).

• Mentorship & Knowledge Sharing: A culture where senior members actively mentor junior colleagues and where best practices and learnings are shared openly to elevate the team's collective craft.

• Data-Informed, Not Data-Dictated: While data is paramount, the team values critical interpretation and the nuanced understanding that qualitative research provides, avoiding uncritical acceptance of quantitative outputs.

📝 Enhancement Note: The culture emphasizes intellectual curiosity, methodological excellence, and a proactive, impactful approach to research. The integration of AI is not just a tool but a core part of how the team operates and innovates.

⚡ Challenges & Growth Opportunities

Challenges:

• Bridging Cultural/Geographic Gaps: Effectively researching US consumers from an office in Bangalore requires sensitivity, adaptability, and strong remote research execution skills.

• Integrating AI Critically: Ensuring AI tools are used effectively and ethically, avoiding over-reliance, and maintaining research integrity while leveraging AI's power.

• Translating Complex Insights: Communicating nuanced behavioral insights and AI-driven findings to stakeholders with diverse technical backgrounds and priorities.

• Driving Adoption: Ensuring research recommendations lead to concrete product or strategy changes, overcoming potential organizational inertia.

• Setting New Standards: Establishing best practices for mixed-methods research and AI integration within a growing team.

Learning & Development Opportunities:

• Advanced Methodological Training: Opportunities to deepen expertise in mixed-methods, behavioral science, and AI in research.

• Exposure to Large-Scale Data: Working with data and user bases of hundreds of millions provides unique learning opportunities.

• Strategic Impact Experience: Gaining experience in shaping strategy at a significant scale within a major consumer tech platform.

• Leadership & Mentorship: Developing leadership skills through mentoring junior researchers and influencing team practices.

• Industry Conferences & Publications: Potential to attend leading conferences or contribute to research publications, enhancing professional visibility.

📝 Enhancement Note: The challenges are framed as opportunities for growth, particularly in navigating complex research environments and leading methodological innovation. The growth opportunities highlight the potential for significant professional development.

💡 Interview Preparation

Strategy Questions:

• "Describe a complex strategic question you've tackled using mixed-methods research. How did you frame the problem, what methods did you use, and what was the ultimate impact?"

• "How do you approach integrating AI into your research workflow? Provide specific examples of tools or processes you've used, and discuss a time you critically evaluated AI output."

• "Imagine you're tasked with understanding why users are dropping off at a specific point in our inspiration-led shopping funnel. How would you use behavioral science principles and mixed-methods research to investigate this?"

• "How do you ensure your research recommendations are adopted by product or growth teams? Walk us through a case where your insights led to significant change." Company & Culture Questions:

• "What interests you about Glance's unique approach to AI commerce and inspiration-led shopping?"

• "How do you see yourself contributing to the Foresight & Behavioral Insights Unit's mission of decoding consumer behavior?"

• "Describe your experience mentoring junior researchers. What is your philosophy on developing talent?"

• "How would you approach building trust and credibility with Data Science and Product teams as a senior research partner?" Portfolio Presentation Strategy:

• Focus on Impact: Clearly articulate the business problem and the tangible impact of your research. Quantify outcomes whenever possible.

• Detail Your Process: Be prepared to explain the rationale behind your methodological choices, especially how qualitative and quantitative methods were integrated to provide a richer understanding.

• Show, Don't Just Tell (AI): Demonstrate your AI integration with specific examples. Discuss prompt engineering, AI-assisted synthesis, or how you identified AI limitations.

• Anticipate Questions: Think about potential follow-up questions regarding your decision-making, challenges faced, and alternative approaches you might have considered.

• Highlight Collaboration: Emphasize how you partnered with stakeholders throughout the research process.

📝 Enhancement Note: Interview preparation should focus on demonstrating strategic thinking, practical AI application, strong methodological grounding, and the ability to influence. Candidates need to be ready to articulate their impact and process with specific examples from their portfolio.

📌 Application Steps

To apply for this Senior Mixed Methods Researcher position:

• Submit your application through the provided link on Greenhouse.

• Tailor Your Resume: Highlight your 7+ years of research experience, specifically emphasizing your mixed-methods expertise, behavioral science background, AI integration in research, and any mentoring experience. Use keywords from the job description.

• Prepare Your Portfolio: Select 2-3 strong case studies that showcase your ability to lead strategic research, integrate qualitative and quantitative methods, demonstrate tangible business impact, and effectively leverage AI tools. Be ready to present these.

• Research Glance & InMobi: Understand Glance's AI commerce platform, its inspiration-led shopping model, and its position within the InMobi Group. Familiarize yourself with their target markets (US and Asia) and their use of AI.

• Practice Your Narrative: Rehearse your "story" for the interview, focusing on how your skills and experience align with the role's requirements, particularly your approach to AI in research and your mentorship capabilities.

⚠️ 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.