Design Researcher

📍 Job Overview

Job Title: Design Researcher

Company: PALO IT

Location: Ciudad de México, CDMX, Mexico

Job Type: Full-time

Category: Research Operations & Insights Enablement

Date Posted: March 25, 2026

Experience Level: 5-10 years

Remote Status: On-site

🚀 Role Summary

• Establish, scale, and govern the Research Ops practice to enable continuous, reliable, and decision-oriented research across the organization.

• Build the operational backbone for mixed-method research, integrating AI as an accelerator for analysis and synthesis.

• Define and implement ethical standards, consent practices, research governance, and participant data management.

• Design and optimize research workflows from intake and prioritization to repository, synthesis, and activation.

• Build and maintain the research tooling ecosystem, leveraging platforms such as Dovetail, Maze, Looker, and Hotjar.

📝 Enhancement Note: The job title "Design Researcher" is slightly misleading given the detailed responsibilities. The core function is heavily focused on establishing and managing Research Operations (Research Ops) and Insights Enablement, with a strong emphasis on operationalizing research processes, managing research tools, and integrating AI for analysis. This role is less about conducting individual research studies and more about creating the systems and infrastructure that empower research teams.

📈 Primary Responsibilities

• Define and scale the Research Ops model, encompassing governance, standards, workflows, and clear ownership structures.

• Establish and enforce ethical standards, robust consent practices, comprehensive research governance, and secure participant data management protocols.

• Build operational systems to support continuous discovery and the implementation of ongoing research programs at scale.

• Enable effective mixed-method research by facilitating the structured triangulation of qualitative and quantitative signals to derive deeper insights.

• Design and optimize end-to-end research workflows, covering intake, prioritization, repository management, synthesis, and the activation of research findings.

• Build and maintain a sophisticated research tooling ecosystem, including critical platforms such as Dovetail, Maze, Looker, and Hotjar, ensuring seamless integration and utilization.

• Integrate AI-assisted analysis and synthesis capabilities, leveraging technologies like GPT and automation to accelerate pattern detection, summarization, and the efficient distribution of insights.

• Create scalable systems for knowledge management, including taxonomy development, effective tagging, repository quality assurance, and efficient evidence retrieval.

• Define, track, and report on OKRs and KPIs that are directly tied to uncertainty reduction, decision quality improvement, research adoption rates, and overall operational efficiency.

• Foster strong partnerships with Product, Design, Data, and Engineering teams to embed research insights directly into roadmap planning and critical decision-making cycles.

• Improve the speed, consistency, and overall usability of research insights across all relevant teams and stakeholders.

• Act as a strategic enabler for research maturity across the organization, guiding teams from ad hoc study practices to a trusted, continuous-learning system.

📝 Enhancement Note: The responsibilities clearly indicate a strategic operational role focused on enabling research, rather than a hands-on research execution role. The emphasis on "scaling," "governing," "building operational systems," and "integrating AI" points to a need for process design, system implementation, and continuous improvement expertise within the research domain.

🎓 Skills & Qualifications

Education: While not explicitly stated, a Bachelor's or Master's degree in a relevant field such as Human-Computer Interaction (HCI), Psychology, Sociology, Information Science, Computer Science, or a related discipline is typically expected for roles involving research operations and insights. Specialized certifications in research methodologies or operations management could also be beneficial.

Experience: 5-10 years of proven experience in Research Operations, UX Research Operations, Insights Operations, or Research Program Management. This level of experience suggests a need for significant expertise in establishing and scaling operational frameworks within a research context.

Required Skills:

• Proven experience in Research Ops, UX Research Operations, Insights Operations, or Research Program Management.

• Strong command of advanced mixed methods, including qualitative and quantitative triangulation to derive comprehensive insights.

• Solid understanding of applied statistics and the ability to interpret research findings for decision-making.

• Hands-on experience with research repositories and insight platforms such as Dovetail and Maze.

• Familiarity with analytics and behavior tools such as Looker and Hotjar.

• Experience using AI tools for research analysis, synthesis, and knowledge scaling.

• Strong understanding of research governance, ethics, consent, and operational quality principles.

• Ability to design scalable processes that support continuous discovery and democratized research access.

• Excellent critical thinking skills for problem-solving and strategic planning.

• Advanced synthesis and pattern recognition capabilities to distill complex data into actionable insights.

• Excellent stakeholder management skills, with the ability to build relationships and influence across departments.

• Strong analytical judgment to evaluate research quality and impact.

Preferred Skills:

• Experience with AI-powered generative tools beyond basic analysis, such as those for content generation or advanced data modeling.

• Experience in a technology consultancy environment or with a focus on product development lifecycle (SDLC).

• Familiarity with agile methodologies and their application to research operations.

• Experience with data visualization tools beyond Looker, for broader reporting capabilities.

• Knowledge of privacy regulations (e.g., GDPR, CCPA) related to user data.

📝 Enhancement Note: The required skills list is extensive and points to a highly capable individual who can bridge operational excellence with research execution and strategic enablement. The emphasis on AI tools and mixed methods suggests a forward-thinking approach to research operations.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Demonstrations of established and scaled Research Ops models, including documented governance, standards, and workflows.

• Case studies showcasing the successful implementation of ethical standards, consent practices, and participant data management systems.

• Examples of operational systems built for continuous discovery and ongoing research programs, highlighting scalability.

• Evidence of enabling mixed-method research, with examples of qualitative and quantitative data triangulation.

• Optimized research workflows, illustrating improvements in intake, prioritization, repository, synthesis, and activation processes.

• Experience with integrating and managing research tooling ecosystems, with specific examples of platforms like Dovetail, Maze, Looker, and Hotjar.

• Projects demonstrating the integration of AI-assisted analysis and synthesis for research, showcasing accelerated insights.

• Systems developed for knowledge management, taxonomy, tagging, repository quality, and evidence retrieval.

Process Documentation:

• Detailed documentation of research workflow design and optimization phases, including process mapping and efficiency improvements.

• Evidence of implementing and automating research processes, showcasing efficiency gains and reduced manual effort.

• Metrics and analysis of research process performance, demonstrating measurement and continuous improvement cycles.

📝 Enhancement Note: Given the operational nature of this role, a portfolio that demonstrates process design, system implementation, and measurable impact is crucial. Candidates should be prepared to showcase how they've built, scaled, and improved research operations, with concrete examples of tools, processes, and outcomes.

💵 Compensation & Benefits

Salary Range: For a role requiring 5-10 years of experience in Research Operations and Insights Enablement in Mexico City, a competitive salary range can be estimated. Based on industry benchmarks for specialized operations roles and the cost of living in Mexico City, a range of MXN $60,000 - $90,000 per month (approximately USD $3,300 - $5,000 per month) is a reasonable expectation. This range accounts for the specialized skill set, the operational complexity, and the strategic impact of the role.

Benefits:

• Stimulating working environments that encourage innovation and collaboration.

• Unique career path opportunities within a growing global technology consultancy.

• International mobility options for employees seeking global experience.

• Opportunity to work on internal R&D projects, fostering continuous learning and development.

• Robust knowledge-sharing platforms and initiatives to support professional growth.

• Personalized training programs tailored to individual development needs.

• Entrepreneurship and intrapreneurship opportunities, encouraging proactive contribution and innovation.

• Access to an employee happiness measurement and improvement program.

Working Hours: The role is specified as full-time, with an implied standard workweek of 40 hours. While the role is on-site, there may be flexibility depending on project needs and team collaboration, common in dynamic consultancy environments.

📝 Enhancement Note: Salary figures are estimates based on industry data for similar roles in Mexico City. Actual compensation may vary based on the candidate's specific experience, qualifications, and the company's compensation structure. The benefits listed are drawn directly from the provided company description, highlighting a strong focus on employee development and well-being.

🎯 Team & Company Context

🏢 Company Culture

Industry: Technology Consultancy with a strong focus on sustainable and impactful digital product development. PALO IT operates within a niche that blends cutting-edge technology (.e.g., AI, Gen-e2) with a commitment to the triple bottom line (people, planet, profit). This industry context means operations professionals will likely engage with innovative projects, diverse client needs, and a culture that values both technical excellence and social responsibility.

Company Size: Over 650 experts across 18 offices on 5 continents. This size indicates that PALO IT is a significant global player with established processes but also retains agility. For operations roles, this means opportunities to work within a structured framework, contribute to global initiatives, and potentially navigate complex cross-border operations, while still having a voice in process improvement.

Founded: The founding date is not explicitly provided, but the company's description as a "World Economic Forum New Champion" and "B Corp-certified company" suggests a mature organization with a forward-thinking and ethical business model, likely founded some years ago to achieve such recognitions.

Team Structure:

• The Research Ops & Insights Enablement role will likely be part of a broader Operations, Product, or Design function.

• Reporting structure is not specified but is expected to be within a team focused on enhancing research capabilities and delivering insights.

Methodology:

• PALO IT emphasizes an "AI First" approach to the Software Development Lifecycle (SDLC) through their Gen-e2 methodology, generating a significant portion of product artifacts with AI.

• Data analysis and insights methods are central to their operations, aiming for continuous learning and decision-oriented research.

• Workflow planning and optimization are critical, with a focus on speed, quality, and efficiency, enhanced by AI.

• Automation and efficiency practices are deeply embedded, particularly through their Gen-e2 framework.

Company Website: palo-it.com

📝 Enhancement Note: The company's commitment to sustainability, B Corp certification, and the innovative Gen-e2 methodology are key cultural differentiators. Operations professionals joining PALO IT should expect to work in an environment that values ethical practices, technological advancement, and measurable impact.

📈 Career & Growth Analysis

Operations Career Level: This role is positioned as a senior-level individual contributor, a "Research Ops & Insights Enablement" specialist. It requires significant experience (5-10 years) in establishing and scaling operational practices. The scope is strategic, focusing on building the "backbone" of research operations, defining governance, and integrating advanced tools like AI. This is not an entry-level or junior support role but a foundational position for shaping how research is done.

Reporting Structure: While not explicitly stated, a role focused on building operational infrastructure often reports to a Director or Head of Research, Product Operations, or a similar senior leadership position. The emphasis on cross-functional partnership suggests the role will have significant visibility and influence across multiple departments.

Operations Impact: The impact of this role is directly tied to improving the speed, rigor, and decision-making quality of the entire organization by making research insights more accessible, reliable, and actionable. By operationalizing research and integrating AI, this role contributes to reducing organizational uncertainty, accelerating product development cycles (as highlighted by the Gen-e2 methodology's 2-3x faster delivery), and ultimately driving better business outcomes and innovation.

Growth Opportunities:

• Operations Leadership: Potential to grow into a Head of Research Operations or Director of Insights Enablement, leading a team and setting the strategic direction for research operations globally within PALO IT.

• Specialization: Deepen expertise in AI integration for research, advanced analytics, or specific research methodologies, becoming a subject matter expert.

• Cross-functional Advancement: Transition into roles in Product Operations, Data Strategy, or even Product Management, leveraging a deep understanding of user insights and operational efficiency.

• Global Impact: As PALO IT expands, opportunities to lead research operations initiatives in new regions or for specific global product lines.

📝 Enhancement Note: The role offers a significant opportunity for impact and growth, particularly for individuals passionate about operationalizing research and leveraging emerging technologies like AI. The company's structure and methodology suggest a clear path for those who can demonstrate success in building scalable, efficient research operations.

🌐 Work Environment

Office Type: PALO IT emphasizes "stimulating working environments" and has a global presence with 18 offices. The role is specifically for Ciudad de México, suggesting a modern, collaborative office space designed to foster innovation and teamwork. Given the company's focus on technology and consultancy, the office is likely equipped with advanced technology infrastructure to support both on-site collaboration and client engagements.

Office Location(s): The primary location is Ciudad de México, CDMX, Mexico. Specific office details are not provided, but it's reasonable to assume a well-situated office accessible via public transport or with adequate parking, catering to the needs of its global workforce.

Workspace Context:

• Collaborative Environment: The emphasis on "collective intelligence," "knowledge sharing," and cross-functional partnerships indicates a workspace designed for open communication, team-based problem-solving, and idea exchange.

• Operations Tools & Technology: Candidates can expect access to a robust suite of research, analytics, and AI tools, including Dovetail, Maze, Looker, Hotjar, and GPT-based platforms, essential for executing the role's responsibilities.

• Team Interaction: Opportunities for regular interaction with diverse teams, including researchers, designers, product managers, data scientists, and engineers, facilitating a rich learning and collaborative experience.

Work Schedule: The role is full-time, typically around 40 hours per week. While on-site, consultancy environments often require adaptability to client needs and project deadlines, which may occasionally involve flexible working hours or extended periods on specific projects. The company's commitment to employee happiness and work-life balance suggests a supportive approach to managing workloads.

📝 Enhancement Note: The on-site requirement in Mexico City suggests a need for candidates comfortable with a traditional office setup, balanced with the company's broader culture of flexibility and innovation. The workspace is expected to be modern and conducive to collaboration and technological advancement.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A review of your resume and portfolio, focusing on relevant experience in Research Ops, Insights Operations, or Research Program Management, and your understanding of mixed methods and operational scaling.

• Technical/Skills Interview: Discussion of your experience with specific research tools (Dovetail, Maze, Looker, Hotjar), AI in research, and your approach to establishing governance, workflows, and knowledge management systems. Expect scenario-based questions related to operational challenges.

• Portfolio Presentation: A dedicated session where you will present case studies from your portfolio, showcasing how you've built, scaled, and optimized research operations. Focus on demonstrating your impact through metrics and clear process descriptions.

• Team/Cultural Fit Interview: Conversations with potential team members and hiring managers to assess your collaboration style, critical thinking, stakeholder management skills, and alignment with PALO IT's values (positive, courageous, caring, doers, committed to excellence).

• Final Interview: A discussion with senior leadership to review your overall fit, strategic vision for Research Ops at PALO IT, and confirm alignment with company goals.

Portfolio Review Tips:

• Showcase Operations, Not Just Research: Highlight your experience in building systems, processes, and infrastructure for research, rather than just the research studies themselves.

• Quantify Impact: Use metrics and data to demonstrate the success of your initiatives (e.g., reduced research cycle time by X%, increased insight adoption by Y%, improved data quality by Z%).

• Process Clarity: Clearly outline the problem, your proposed operational solution, the implementation steps, the tools used, and the resulting outcomes.

• AI Integration: Specifically detail how you've leveraged AI tools in research analysis, synthesis, or knowledge management, and the benefits achieved.

• Tool Proficiency: Provide concrete examples of your proficiency with key platforms like Dovetail, Maze, Looker, and Hotjar.

• Governance & Ethics: Include examples of how you've established and managed research governance, ethical guidelines, and data privacy protocols.

Challenge Preparation:

• Be prepared for a potential case study or a set of hypothetical scenarios focused on operationalizing research. This might involve designing a Research Ops framework for a new product team, optimizing an existing workflow, or proposing how to integrate AI into a scaled research process.

• Practice articulating complex operational strategies and solutions clearly and concisely, focusing on scalability and impact.

• Think about how you would measure success for a Research Ops function and how you would communicate that success to stakeholders.

📝 Enhancement Note: This section provides a structured approach to preparing for the interview process, emphasizing the unique requirements of a Research Ops role, particularly the need for a strong operational portfolio and strategic thinking.

🛠 Tools & Technology Stack

Primary Tools:

• Dovetail: For managing research findings, creating a centralized repository, and synthesizing qualitative data. Proficiency in setting up projects, tagging, and generating reports is expected.

• Maze: For unmoderated user testing, collecting rapid feedback on prototypes, and analyzing user behavior data. Experience in setting up studies, configuring tests, and interpreting results is key.

• Looker: A business intelligence platform for data analytics and visualization. Essential for tracking KPIs, creating dashboards, and reporting on research impact and operational efficiency.

• Hotjar: For understanding user behavior on websites through heatmaps, session recordings, and user feedback widgets. Useful for qualitative behavioral analysis and identifying areas for deeper research.

• AI Tools (e.g., GPT-based platforms): For accelerating research analysis, summarization, pattern detection, knowledge extraction, and potentially content generation for research outputs. Understanding prompt engineering and ethical AI usage in research is crucial.

Analytics & Reporting:

• Looker: As mentioned, for comprehensive analytics and reporting on research operations performance and insights.

• Other BI/Analytics Tools: Familiarity with other BI tools or statistical analysis software (e.g., R, Python for data analysis) could be beneficial for deeper quantitative insights.

CRM & Automation:

• While not explicitly mentioned as a primary focus, understanding how research insights integrate with CRM data or how automation can streamline research workflows (e.g., participant recruitment, scheduling) is valuable.

• Integration Tools: Experience with tools that connect different platforms to ensure data flow and operational efficiency within the research ecosystem.

📝 Enhancement Note: The explicit mention of Dovetail, Maze, Looker, and Hotjar, along with AI tools, indicates the core technology stack. Candidates should be prepared to discuss their hands-on experience with these specific platforms and their ability to integrate and manage them effectively.

👥 Team Culture & Values

Operations Values:

• Excellence: A commitment to delivering high-quality, reliable, and actionable research operations and insights, aligning with PALO IT's dedication to excellence.

• Data-Driven Approach: Emphasizing the use of data and metrics (OKRs, KPIs) to measure the impact of research operations and guide decision-making.

• Efficiency & Automation: A focus on streamlining workflows, leveraging AI, and implementing scalable processes to improve research velocity and reduce operational friction.

• Collaboration & Partnership: Working closely with Product, Design, Data, and Engineering teams to embed research into the product development lifecycle and foster a shared understanding of user needs.

• Continuous Learning: Embracing new technologies, methodologies, and best practices in research operations and AI to stay at the forefront of the field.

Collaboration Style:

• Cross-functional Integration: Actively seeking opportunities to integrate research operations across different departments, breaking down silos and ensuring insights are accessible.

• Process Review & Feedback: Fostering a culture where research processes are regularly reviewed, iterated upon, and improved based on feedback from researchers and stakeholders.

• Knowledge Sharing: Proactively sharing best practices, learnings, and insights from research operations to empower other teams and build organizational research maturity.

📝 Enhancement Note: PALO IT's values of being positive, courageous, caring, doers, and committed to excellence are likely reflected in their operations teams. Candidates should demonstrate these qualities, particularly in their approach to problem-solving, collaboration, and driving change.

⚡ Challenges & Growth Opportunities

Challenges:

• Scaling Research Ops in a Growing Company: As PALO IT scales globally, establishing consistent, high-quality research operations across different regions and teams will be a significant challenge.

• Integrating AI Effectively and Ethically: Balancing the excitement of AI acceleration with the critical need for ethical AI usage, data privacy, and maintaining research integrity.

• Democratizing Research Access: Enabling broader access to research tools and insights without compromising quality or governance, ensuring democratized research is also rigorous research.

• Measuring Operational Impact: Clearly defining and demonstrating the tangible value of Research Ops to the business, translating operational metrics into business outcomes.

• Navigating Ambiguity: Building foundational operational frameworks in a dynamic, fast-paced technology consultancy environment requires adaptability and clear strategic thinking.

Learning & Development Opportunities:

• AI in Research Specialization: Deepen expertise in leveraging cutting-edge AI tools for advanced research analysis, synthesis, and automation.

• Global Operations Management: Gain experience managing operational processes across a global organization, understanding diverse cultural and market contexts.

• Research Strategy & Governance: Develop expertise in designing and implementing robust research governance frameworks that balance efficiency with ethical compliance.

• Product Operations Leadership: Potentially transition into broader product operations roles, applying operational expertise to other facets of the product lifecycle.

• Industry Conferences & Certifications: Opportunities to attend leading industry events (e.g., UXPA, CHI, industry-specific ops conferences) and pursue relevant certifications to enhance professional development.

📝 Enhancement Note: The challenges and growth opportunities highlight the dynamic and impactful nature of this role. Candidates should be prepared to tackle complex operational problems and leverage them as springboards for professional development.

💡 Interview Preparation

Strategy Questions:

• "How would you design and implement a Research Ops model from scratch for a growing technology consultancy like PALO IT?"

  • Preparation: Focus on a phased approach, covering governance, tooling, workflows, team structure, and key metrics. Emphasize scalability and adaptability.

• "Describe a time you successfully integrated AI tools into a research workflow. What were the challenges, and what was the impact?"

  • Preparation: Prepare a specific case study detailing the AI tool, the problem it solved, the implementation process, ethical considerations, and quantifiable results (e.g., time savings, insight quality improvement).

• "How do you ensure research quality and ethical standards are maintained when democratizing research access across multiple teams?"

  • Preparation: Discuss training programs, standardized templates, review processes, consent management systems, and clear guidelines for researchers.

Company & Culture Questions:

• "What excites you about PALO IT's mission and its 'AI First' approach (Gen-e2)?"

  • Preparation: Research PALO IT's sustainability goals, B Corp status, and the Gen-e2 methodology. Connect your passion for operational excellence and innovation to these aspects.

• "How would you collaborate with Product, Design, Data, and Engineering teams to ensure research insights are actionable and integrated into decisions?"

  • Preparation: Provide examples of your stakeholder management skills, communication strategies, and how you've fostered cross-functional alignment in previous roles.

• "How do you measure the success and impact of Research Operations initiatives?"

  • Preparation: Be ready to discuss specific OKRs and KPIs you've used or would propose, focusing on metrics that demonstrate uncertainty reduction, decision quality, and operational efficiency.

Portfolio Presentation Strategy:

• Structure Your Narrative: For each case study, clearly define the problem, your solution (the operational framework or process you built/improved), the implementation details, the tools used, and the measurable outcomes.

• Highlight Operational Impact: Emphasize your role in building, scaling, and optimizing systems, not just conducting research. Use clear metrics to quantify improvements in efficiency, quality, and accessibility.

• Demonstrate Tool Proficiency: Be prepared to walk through how you've used tools like Dovetail, Maze, Looker, and AI platforms to achieve specific operational goals.

• Showcase AI Integration: Clearly articulate how AI was leveraged, the benefits, and any ethical considerations addressed.

• Connect to PALO IT: Tailor your examples to align with PALO IT's stated values and their innovative approach to technology and sustainability.

📝 Enhancement Note: This preparation guide focuses on the strategic, operational, and technical aspects of the role. Candidates should prepare to demonstrate their ability to build and scale research operations, leverage AI, and align with PALO IT's unique culture and mission.

📌 Application Steps

To apply for this Research Ops & Insights Enablement position:

• Submit your application through the provided job link on greenhouse.io.

• Portfolio Customization: Prepare a portfolio that specifically highlights your experience in establishing, scaling, and governing Research Operations. Include case studies demonstrating your work with research tooling (Dovetail, Maze, Looker, Hotjar), AI integration for analysis and synthesis, and the development of research workflows and knowledge management systems. Quantify your impact with relevant metrics.

• Resume Optimization: Tailor your resume to emphasize keywords related to Research Ops, UX Research Operations, Insights Operations, Research Program Management, mixed methods, AI in research, and specific tool proficiencies mentioned in the job description. Clearly articulate your achievements in process optimization and operational scaling.

• Interview Preparation: Practice articulating your approach to building a Research Ops function, your experience with AI tools, and your stakeholder management strategies. Prepare to present 1-2 key portfolio projects in detail, focusing on your operational contributions and the measurable impact achieved.

• Company Research: Thoroughly research PALO IT's mission, values, B Corp certification, and the Gen-e2 methodology. Understand how your role contributes to their vision of "tech as a force for good" and their "AI First" approach. Prepare thoughtful questions about their research culture and operational challenges.

⚠️ 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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