📍 Job Overview
Job Title: Senior UX Researcher (L5)
Company: Instacart
Location: United States - Remote
Job Type: Full-time
Category: UX Research
Date Posted: 2025-06-13T16:50:16
Experience Level: Senior (5-10 years)
Remote Status: Remote
🎨 Role Summary
- Lead end-to-end qualitative and quantitative UX research initiatives focused on machine learning-powered product features within the online grocery domain.
- Design and execute complex research studies to evaluate the usability, effectiveness, and user perception of ML outputs, such as recommendations and predictions.
- Translate intricate research findings into actionable insights, design principles, and guidelines to inform product strategy, model training, and interface design.
- Collaborate closely with cross-functional teams, including Product, Design, Data Science, and Engineering, to integrate user understanding into the product development lifecycle for AI-driven experiences.
🖼️ Primary Responsibilities
- Conduct comprehensive qualitative research (e.g., in-depth interviews, usability testing, contextual inquiry) to deeply understand user needs, mental models, and pain points related to ML-powered features in the online grocery shopping journey.
- Design and implement quantitative research studies (e.g., surveys, A/B testing analysis, behavioral data analysis) to measure user behavior, evaluate the impact of ML outputs, and identify patterns at scale.
- Develop and refine research methodologies specifically tailored for evaluating the user experience of algorithms and AI models, focusing on transparency, trust, and control.
- Synthesize research findings from various sources into compelling narratives and actionable recommendations that resonate with technical and non-technical stakeholders, including data scientists and engineers.
- Establish continuous feedback loops between users, the research team, and data science teams to inform iterative improvements of ML models based on real-world user interactions and experiences.
- Partner with Product Designers to conceptualize and test user interfaces that effectively communicate the rationale and functionality of ML outputs, ensuring users understand and trust the system.
- Champion ethical AI principles and practices within the product development process, ensuring user research informs the responsible and equitable deployment of machine learning features.
🎓 Skills & Qualifications
Education: Bachelor's or Master's degree in Psychology, Cognitive Science, Human-Computer Interaction (HCI), Statistics, Data Science, Anthropology, or a closely related field. A Master's or PhD is preferred, indicating a desire for advanced research skills and theoretical grounding.
Experience: Minimum of 5 years of dedicated professional experience in UX research, with a significant portion focused on designing for and researching machine learning-powered products and large-scale consumer applications. Experience should demonstrate a strong portfolio of past research projects, particularly those involving complex systems and data-driven insights.
Required Skills:
- Expert proficiency in a wide range of qualitative research methods, including but not limited to usability testing, in-depth interviewing, focus groups, diary studies, and ethnographic research.
- Strong command of quantitative research methodologies, including survey design, experimental design (e.g., A/B testing), statistical analysis, and the ability to interpret large datasets.
- Demonstrable experience researching machine learning-powered products with large user bases (millions of active users), such as recommendation engines, personalization features, or conversational interfaces.
- Solid understanding of ethical AI principles, data privacy considerations, and best practices for researching potentially biased or opaque systems.
- Exceptional communication, presentation, and storytelling skills, with the ability to clearly articulate complex research findings and their implications to diverse audiences.
- Proven ability to manage multiple research projects simultaneously, prioritize effectively, and deliver high-quality insights within fast-paced environments.
- Experience collaborating effectively within cross-functional teams, including Product Managers, Designers, Data Scientists, and Engineers throughout the product lifecycle.
Preferred Skills:
- Advanced degree (Master's or PhD) in a research-related field, demonstrating a deeper theoretical and methodological foundation.
- Experience with research methodologies specifically designed for evaluating algorithmic fairness, transparency, and user control in AI systems.
- Familiarity with statistical software (e.g., R, Python for data analysis) or advanced data analysis techniques relevant to UX research.
- Experience working in the e-commerce or grocery technology industry, with an understanding of the unique user behaviors and challenges in this domain.
🎨 Portfolio & Creative Requirements
Portfolio Essentials:
- Present a curated selection of 3-5 in-depth case studies showcasing your end-to-end UX research process, from initial problem framing and research design to execution, analysis, and impact.
- Highlight projects specifically involving the research of machine learning or AI-powered features, demonstrating your approach to understanding user interaction with complex, data-driven systems.
- Clearly articulate the research questions, methodologies used (both qualitative and quantitative), participant recruitment strategies, and key findings for each project.
- Quantify the impact of your research on product decisions, user outcomes, or business metrics whenever possible, demonstrating the value of your insights.
Process Documentation:
- Showcase your approach to the research and discovery phase, including how you identify research opportunities, define scope, and select appropriate methodologies for complex problems.
- Document your process for analyzing qualitative data (e.g., thematic analysis, affinity mapping) and quantitative data (e.g., statistical analysis, data visualization) to derive meaningful insights.
- Illustrate how you translate research findings into actionable recommendations and communicate them effectively to diverse stakeholders, including technical teams.
💵 Compensation & Benefits
Salary Range: $139,000 - $185,000 USD per year. This range is based on the provided information and is dependent on the candidate's permanent work location within the United States, reflecting regional cost of living and market rates for Senior UX Researchers with experience in ML/AI. Specific ranges for California, New York, Connecticut, New Jersey, Washington, Oregon, Delaware, Maine, Massachusetts, Maryland, New Hampshire, Rhode Island, Vermont, DC, Pennsylvania, Virginia, Colorado, Texas, Illinois, Hawaii, and other states are provided by the company.
Benefits:
- Highly competitive market-based compensation.
- Equity grants, including a new hire grant and annual refresh grants, aligning employee success with company performance.
- Comprehensive benefits package (details available on the Instacart careers site), typically including health, dental, and vision insurance, retirement plans, and other wellness programs.
- Flexible work environment ("Flex First") allowing remote work with regular in-person events for connection and community building.
Working Hours: Full-time position, typically requiring approximately 40 hours per week. While remote work offers flexibility, collaboration with teams across different time zones may be necessary, requiring adaptability in working hours.
🎯Team & Company Context
🏢 Company & Design Culture
Industry: Grocery Technology / E-commerce. Instacart is a leader in the online grocery delivery and pickup space, operating within a rapidly evolving and highly competitive market. This context means design and research play a critical role in understanding complex user behaviors related to food, shopping, and delivery.
Company Size: Over 1,500 national, regional, and local retail banners partnered, facilitating services from over 85,000 stores, with approximately 600,000 shoppers. With over 22,000 LinkedIn employees, Instacart is a large, established public company. This size suggests a structured design and research organization with established processes, but also potential for impact at scale.
Founded: Company founding date is not explicitly provided in the input, but Instacart has been a significant player in the market for several years, indicating a mature organization with a history of innovation in the grocery tech space.
Team Structure:
- The UX Research team is described as collaborative and tight-knit, partnering closely with Product, Design, Data Science, and Engineering. This indicates a highly cross-functional environment where research insights are integral to product development.
- The role sits within the Online Grocery team, suggesting a focus on consumer-facing experiences related to browsing, purchasing, and managing grocery orders online.
- As a Senior (L5) researcher, this role likely involves mentoring more junior researchers, leading significant research initiatives independently, and contributing to the overall research strategy.
Methodology:
- The team emphasizes understanding the future of online grocery shopping and rapidly evolving behaviors, suggesting a focus on strategic, generative research in addition to evaluative research.
- A strong partnership with Data Science is highlighted, implying a mixed-methods approach that combines qualitative insights with quantitative data analysis to inform product decisions.
- The focus on ML-powered products indicates a need for methodologies that can effectively evaluate complex algorithmic outputs and user trust in AI systems.
Company Website: https://www.instacart.com
📈 Career & Growth Analysis
Design Career Level: Senior UX Researcher (L5). This level typically signifies a researcher who can independently lead complex research projects, mentor others, significantly influence product strategy, and contribute to the development of research practices within the organization. An L5 researcher is expected to operate with a high degree of autonomy and strategic thinking.
Reporting Structure: While the direct reporting structure isn't specified, a Senior UX Researcher at this level likely reports to a Research Manager or Director, providing both guidance and autonomy to manage their research initiatives.
Design Impact: This role has the potential for significant impact by shaping the user experience of core, ML-powered features used by millions of Instacart customers. Insights generated will directly influence product roadmaps, algorithm design, and the overall usability and trustworthiness of the online grocery platform.
Growth Opportunities:
- Potential for advancement to a Lead or Principal UX Researcher role, taking on more strategic initiatives, mentoring a team, and shaping the future of research at Instacart.
- Opportunity to deepen expertise in the specialized area of researching AI/ML products, becoming a subject matter expert in this cutting-edge field.
- Growth through contributing to the development and refinement of the research team's methodologies, tools, and best practices, particularly in the context of ML.
🌐 Work Environment
Studio Type: Remote-first with options for in-office work or other locations ("Flex First"). This model prioritizes flexibility while encouraging in-person connection through regular events. The "studio" environment is distributed, relying heavily on digital collaboration tools.
Office Location(s): While the role is remote, Instacart has headquarters in San Francisco, CA, and offices in Toronto, Canada. Employees may have access to these locations for in-person events, but the primary workspace is remote.
Design Workspace Context:
- Collaboration relies heavily on virtual tools for meetings, brainstorming, and sharing research findings.
- The remote environment requires strong self-discipline, time management, and communication skills to stay connected with the team and stakeholders.
- Regular in-person events provide opportunities for team bonding, strategic planning, and fostering a sense of community despite the distributed nature of the team.
Work Schedule: Flexible, allowing employees to choose where they work best. While there are likely core hours for team collaboration, the "Flex First" approach suggests autonomy in managing one's work schedule to balance personal and professional commitments.
📄 Application & Portfolio Review Process
Design Interview Process:
- Initial screening call with a Recruiter to discuss your background, experience, and interest in the role. Be prepared to articulate your experience researching complex systems and ML products.
- Interview(s) with members of the UX Research team to deep dive into your research philosophy, methodologies, and past projects, particularly those showcasing your expertise in ML/AI research. Expect questions about your process, challenges faced, and impact.
- Interviews with cross-functional partners (Product, Design, Data Science, Engineering) to assess your collaboration skills, ability to translate insights for different audiences, and understanding of product development in an ML context.
- A potential presentation or portfolio review session where you walk through key case studies, focusing on the problem, your research approach, findings, recommendations, and the resulting impact. Be ready to discuss the nuances of researching ML features.
- A potential research challenge or take-home exercise related to a hypothetical or real-world problem involving ML-powered products, assessing your research design and analytical skills.
- Final interview(s) with hiring managers or leadership to evaluate overall fit, strategic thinking, and potential contributions to the team and company.
Portfolio Review Tips:
- Curate your portfolio to prominently feature projects where you researched ML or AI-driven products. Clearly explain the specific ML feature, your research objectives, and how you adapted your methodologies to the complexities of AI.
- For each case study, provide a clear narrative of the research process, emphasizing the problem you were trying to solve, the research questions you addressed, and the specific methods you employed (both qualitative and quantitative).
- Focus on demonstrating your ability to translate research insights into actionable recommendations that influenced product decisions, particularly those related to ML model refinement, interface design for ML outputs, or ethical considerations.
- Quantify the impact of your research whenever possible, using metrics related to user behavior, usability improvements, or business outcomes.
Challenge Preparation:
- If given a research challenge involving ML, focus on clearly defining the research problem, proposing appropriate methodologies (considering the unique aspects of researching AI), outlining your data collection and analysis plan, and articulating how you would translate findings into actionable insights for product and data science teams.
- Practice presenting your research process and findings concisely and compellingly. Be prepared to discuss trade-offs in your research design and justify your methodological choices.
- Consider how you would address potential ethical considerations related to the ML feature in your research design and analysis.
ATS Keywords: UX Research, Qualitative Research, Quantitative Research, Usability Testing, Interviews, Surveys, Data Analysis, Machine Learning, AI, Ethical AI, Product Research, Generative Research, Evaluative Research, Mixed Methods, Research Design, Statistical Analysis, User Needs, Pain Points, User Behavior, Product Strategy, Collaboration, Cross-functional Teams, Instacart, E-commerce, Grocery Technology, Remote Work, Flex First, L5, Senior UX Researcher, Case Studies, Portfolio, Research Impact, Stakeholder Management, Communication, Problem Solving, Critical Thinking, User-Centered Design, Human-Computer Interaction (HCI), Cognitive Science, Psychology, Anthropology, Statistics, Data Science, Algorithmic Fairness, Trust in AI, Transparency, Figma, Sketch, InVision (for design collaboration context), SurveyMonkey, Qualtrics (for survey tools), Looker, Tableau (for data visualization context), JIRA, Confluence (for project management context), UserTesting.com, Optimal Workshop (for usability tools).
🛠 Tools & Technology Stack
Primary Design Tools: While this is a research role, familiarity with design tools is beneficial for collaboration. Proficiency in tools like Figma, Sketch, or Adobe XD for understanding and providing feedback on design mockups and prototypes. Experience with collaborative design platforms is a plus.
Collaboration & Handoff:
- Collaboration tools such as Slack, Zoom, or Google Meet for daily communication and virtual meetings with distributed teams.
- Project management and documentation platforms like JIRA and Confluence for tracking research projects, documenting findings, and sharing insights with cross-functional teams.
- Presentation software (e.g., Google Slides, Keynote) for creating and delivering research findings presentations.
Research & Testing:
- Qualitative research tools for conducting remote interviews and usability testing (e.g., Zoom, Lookback, UserTesting.com).
- Survey platforms for designing and distributing quantitative surveys (e.g., Qualtrics, SurveyMonkey).
- Tools for analyzing qualitative data (e.g., Dovetail, thematic analysis software) and quantitative data (e.g., Excel, Google Sheets, statistical software like R or Python for data analysis).
- Familiarity with analytics platforms (e.g., Looker, Tableau, internal dashboards) to access and interpret behavioral data for quantitative research.
👥 Team Culture & Values
Design Values:
- User-Centeredness: A deep commitment to understanding and advocating for the needs, behaviors, and expectations of Instacart users (customers and shoppers).
- Impact-Oriented: A focus on generating research insights that directly inform product decisions, drive meaningful improvements to the user experience, and contribute to business goals.
- Collaboration: A strong emphasis on working closely and effectively with cross-functional partners (Product, Design, Data Science, Engineering) throughout the research and product development lifecycle.
- Curiosity and Continuous Learning: A desire to constantly explore new research methodologies, stay updated on industry trends (especially in ML/AI), and continuously refine research practices.
Collaboration Style:
- Highly collaborative and cross-functional, with researchers embedded within product teams and working closely with designers, product managers, data scientists, and engineers.
- Emphasis on open communication, sharing of insights, and active participation in design critiques and product planning meetings.
- Data-informed decision-making, where research findings are integrated with quantitative data from data science to build a holistic understanding of the user and product performance.
⚡ Challenges & Growth Opportunities
Design Challenges:
- Researching the user experience of complex machine learning models, which can be opaque and unpredictable, requiring innovative research methodologies to understand user trust, comprehension, and control.
- Balancing the need for rigorous research with the fast-paced nature of product development in a dynamic industry like online grocery.
- Translating nuanced qualitative insights about user perception of AI into concrete, actionable recommendations for data scientists and engineers working on model refinement.
- Navigating ethical considerations related to AI, such as bias, privacy, and transparency, and ensuring research informs the responsible development of ML features.
Learning & Development Opportunities:
- Opportunity to become a leading expert in the specialized field of researching user experience for machine learning and AI products.
- Growth through exposure to and collaboration with a strong Data Science team, deepening understanding of ML principles and data analysis techniques.
- Potential for mentorship opportunities, both as a mentee learning from experienced researchers and as a mentor guiding less experienced team members.
- Access to resources for professional development, including conferences, workshops, and online courses, particularly those focused on advanced research methodologies and AI ethics.
💡 Interview Preparation
Design Process Questions:
- Be prepared to discuss your end-to-end research process for a project involving a machine learning feature. Focus on how you adapted your methodology to understand user interaction with AI. Practice walking through a relevant case study from your portfolio.
- Anticipate questions about how you prioritize research questions, select appropriate methodologies (both qualitative and quantitative), and recruit participants for studies involving complex systems.
- Prepare to discuss how you analyze both qualitative and quantitative data to derive insights, particularly how you synthesize findings from different data sources to build a holistic understanding.
Company Culture Questions:
- Research Instacart's mission, values, and recent product announcements, especially those related to AI or personalization. Be ready to discuss how your research approach aligns with their goals and culture.
- Prepare to discuss your experience collaborating with cross-functional teams, particularly Product Managers, Designers, and Data Scientists. Provide examples of how you have effectively communicated research findings to technical and non-technical stakeholders.
- Think about how you approach receiving and providing feedback within a team setting and how you contribute to a collaborative research culture.
Portfolio Presentation Strategy:
- Select 2-3 case studies that best demonstrate your experience researching ML-powered products and your ability to drive impact. Structure your presentation clearly, outlining the problem, your research approach, key findings, recommendations, and the impact of your work.
- For ML-focused projects, dedicate time to explaining the specific ML feature you researched and the unique challenges and considerations involved in evaluating its user experience.
- Practice articulating your research process and findings concisely and compellingly. Be prepared to answer questions about your methodological choices, limitations, and the potential future research directions.
📌 Application Steps
To apply for this design position:
- Submit your application through this link
- Customize your resume to highlight your experience in UX research, particularly your work with machine learning or AI-powered products. Use relevant keywords from the ATS keywords list provided above.
- Prepare a compelling portfolio that showcases your end-to-end research process and demonstrates your ability to conduct rigorous research for complex systems, with a strong emphasis on ML/AI projects.
- Practice presenting your portfolio case studies, focusing on clearly articulating the problem, your research approach, findings, recommendations, and the impact of your work. Be ready to discuss the nuances of researching AI features.
- Research Instacart's business, product, and recent developments, especially in the area of machine learning and online grocery, to demonstrate your interest and understanding during interviews.