Senior User Researcher (Quantitative)

📍 Job Overview

Job Title: Senior User Researcher (Quantitative)

Company: Great Minds

Location: Remote (United States)

Job Type: Full-Time

Category: User Research / Product Analytics

Date Posted: 2026-08-06

Experience Level: Mid-Senior Level (3-5+ years)

Remote Status: Fully Remote

🚀 Role Summary

• Drive user research practices with a strong quantitative focus to mature digital platform analytics and inform product strategy.

• Design, implement, and manage advanced analytics tooling, ensuring robust data governance and self-service enablement for cross-functional teams.

• Execute mixed-methods research studies, analyzing online user behavior and leveraging data from product analytics, surveys, and interviews to identify key improvement opportunities.

• Analyze A/B tests and experiments to inform product decisions, building and interpreting dashboards using tools like Looker, Microsoft BI, and Google Analytics.

• Collaborate closely with Product Managers, Designers, and Engineers to embed research into the digital product development lifecycle, fostering a data-informed decision-making culture.

📝 Enhancement Note: This role bridges the gap between deep quantitative analysis and qualitative user understanding, making it crucial for operations professionals to highlight their ability to translate complex data into actionable insights that drive product strategy and user experience improvements within a SaaS environment.

📈 Primary Responsibilities

• Design and support the implementation of advanced digital product analytics tooling, including defining naming taxonomies and establishing data governance approaches in collaboration with engineering teams.

• Develop and maintain self-service analytics capabilities, including creating comprehensive documentation, training team members on tool usage, and building insightful dashboards for various stakeholders.

• Design and execute mixed-methods research studies, integrating data from product analytics, surveys, usage logs, 1:1 interviews, and observational studies.

• Analyze online user behavior to identify patterns, trends, and opportunities for product enhancement, ensuring data quality through coordination with engineering and refinement of data taxonomies.

• Design, conduct, and analyze A/B tests and experiments to inform product decisions, contributing to a hypothesis-driven discovery and early experimentation process.

• Build and interpret dashboards and reports using analytics platforms such as Looker, Microsoft BI, and Google Analytics to visualize user behavior and product performance.

• Leverage AI and automation tools to identify efficiencies in study design, reporting, analysis, and data visibility, enhancing research operations scalability.

• Contribute to large-scale foundational studies that inform overarching product strategy and roadmap development.

• Translate complex quantitative and qualitative data into clear, compelling narratives and actionable recommendations for Product, Design, and leadership audiences.

• Build strong, collaborative working relationships with Product Managers, Designers, and Engineers to embed research insights into the digital product development lifecycle.

• Partner with non-digital departments (e.g., Sales, Customer Success) to triangulate insights, build confidence in research findings, and support data-informed decision-making across the organization.

• Support recruitment needs for product workstreams, including growing and managing an internal participant panel for research studies.

• Develop and document efficient research practices to scale quality research operations, leveraging AI or automation where beneficial.

• Contribute hands-on to operational needs as the research team scales its practices and processes.

📝 Enhancement Note: The responsibilities highlight a strong emphasis on both the strategic and operational aspects of user research and product analytics. Candidates should be prepared to demonstrate experience in not only conducting research but also in building and maintaining the infrastructure and processes that support data-driven decision-making at scale, particularly within a SaaS product context.

🎓 Skills & Qualifications

Education: Bachelor’s degree required; Master’s degree preferred.

Experience: 3+ years of experience (5+ years preferred) in digital product analytics or quantitative user research for SaaS or web-based software products.

Required Skills:

• Proficiency in designing and executing quantitative user research studies and analyzing digital product analytics.

• Experience with analytics platforms and A/B testing tools such as Google Analytics, Pendo, Maze, Looker, Statsig, Microsoft BI, Excel, and Google Sheets.

• Working proficiency in SQL for querying and analyzing data across multiple sources.

• Demonstrated ability to collaborate effectively across Product, Design, Engineering, and Data teams.

• Proven ability to influence decisions without direct authority by presenting compelling data-driven insights.

• Demonstrated ability to work independently while driving research studies and staying aligned with cross-functional partners.

• Strong analytical and problem-solving skills with the ability to translate complex data into clear, actionable recommendations.

• Excellent communication and presentation skills, with the ability to articulate findings to diverse audiences, including leadership. Preferred Skills:

• Python proficiency for data analysis and scripting.

• Experience with data privacy considerations, particularly for vulnerable populations like minors.

• Familiarity with K–12 or education technology environments and user bases.

• Experience with data governance frameworks and implementation.

• Knowledge of AI applications in research and analytics for efficiency gains.

📝 Enhancement Note: The requirements emphasize a blend of technical data analysis skills (SQL, analytics platforms) and research methodology expertise. Candidates with experience in the education technology sector or with data privacy considerations will have a distinct advantage, showcasing their ability to navigate specific industry challenges.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Case studies demonstrating the design and execution of quantitative user research projects, with a focus on how data insights led to product improvements or strategic shifts.

• Examples of dashboards or reports created using tools like Looker, Microsoft BI, or Google Analytics, showcasing the ability to visualize complex data and communicate key metrics effectively.

• Documentation of experience in setting up and managing analytics tooling, including defining taxonomies and contributing to data governance strategies.

• Evidence of A/B test design, execution, and analysis, clearly outlining hypotheses, methodologies, results, and the resulting product decisions or learnings.

• Projects showcasing mixed-methods research approaches, detailing how quantitative data was integrated with qualitative findings to provide a holistic understanding of user behavior. Process Documentation:

• Workflow examples detailing the process of collaborating with engineering to implement new analytics tracking or tooling.

• Documentation demonstrating experience in creating user guides, training materials, or best practice documents for analytics tools or research methodologies.

• Examples of research plans or study designs that clearly outline objectives, methodologies, participant criteria, and expected outcomes, especially for quantitative studies.

• Artifacts that illustrate the process of translating raw data into compelling narratives and actionable recommendations for product teams.

📝 Enhancement Note: A strong portfolio for this role should not only showcase completed projects but also the candidate's process for data collection, analysis, and communication. Demonstrating the ability to build and maintain research infrastructure, like participant panels or documentation repositories, will be highly valued, reflecting an understanding of scalable research operations.

💵 Compensation & Benefits

Salary Range: The expected base salary range for this position is $109,000 - $120,000 USD annually.

Explanation of Range: This range is determined by factors including location, work experience, skills, and internal equity. It is exclusive of benefits or other incentives.

Benefits:

• Comprehensive health, dental, and vision insurance plans.

• Generous paid time off (PTO) and holidays.

• Opportunities for professional development, including training, conferences, and certifications.

• Retirement savings plan with company match.

• Potential for performance-based bonuses or incentives.

• Access to company-provided resources and tools for remote work efficiency.

Working Hours: Standard full-time work hours, typically around 40 hours per week. Flexibility may be offered, but the role requires consistent availability for cross-functional collaboration and timely data analysis.

📝 Enhancement Note: The salary range provided is competitive for a Senior User Researcher role in the US market, especially for a fully remote position. Candidates should research typical compensation for similar roles in their specific location within the US if applicable, and be prepared to discuss how their experience and skills justify a salary within or potentially above this range. The benefits package should be reviewed for specific details on health coverage, PTO accrual, and retirement contributions.

🎯 Team & Company Context

🏢 Company Culture

Industry: Education Technology (EdTech), Curriculum Development, Publishing.

Company Size: Great Minds is a high-growth organization, indicated by its status as a Public Benefit Corporation and its nationwide reach in the education sector. While an exact number isn't provided, the scale of product adoption (thousands of schools and districts) suggests a significant employee base, likely in the hundreds, with ongoing expansion.

Founded: 2007.

Team Structure:

• The User Research team is part of a larger product development or strategy function, reporting to an Associate Director, User Research.

• This role operates as an individual contributor with a quantitative focus, expected to work closely with Product Managers, Designers, and Engineers.

• Collaboration extends to non-digital departments such as Sales and Customer Success, indicating a holistic approach to understanding the customer journey.

• The team aims to mature research practices, suggesting a culture of continuous improvement and knowledge sharing. Methodology:

• Data-Driven Decision-Making: Strong emphasis on using data from product analytics, user behavior, surveys, and experiments to inform product strategy and development.

• Mixed-Methods Approach: Integration of quantitative analysis with qualitative insights to provide comprehensive understanding.

• User-Centric Design: Commitment to usability, coherence, and practical implementation of educational materials and digital platforms.

• Continuous Improvement: Focus on maturing research practices, scaling operations, and leveraging new technologies like AI for efficiency.

Company Website: https://www.greatminds.org/

📝 Enhancement Note: Great Minds' mission-driven culture, focused on improving education outcomes, is a key differentiator. Operations professionals should align their experience with this mission, highlighting how their analytical and research skills contribute to student success and educator support. The emphasis on growth and product maturity suggests an environment ripe for establishing and refining operations processes.

📈 Career & Growth Analysis

Operations Career Level: This is a Senior-level individual contributor role, focusing on specialized quantitative research and product analytics. It signifies a level of expertise and autonomy where the professional is expected to lead initiatives, mentor others (implicitly through practice maturation), and significantly influence product direction.

Reporting Structure: The role reports to the Associate Director, User Research, placing it within a dedicated research function that likely collaborates closely with Product Management and Design leadership. This structure provides visibility to senior leadership and opportunities to influence strategic decisions.

Operations Impact: The Senior User Researcher's impact is directly tied to improving digital product usability, effectiveness, and adoption. By translating complex user data into actionable insights, they directly influence product strategy, feature development, and the overall user experience for educators and students. This role is critical for ensuring that Great Minds' digital offerings meet user needs and contribute to the company's mission of improving educational outcomes.

Growth Opportunities:

• Specialization Advancement: Deepen expertise in quantitative research methodologies, advanced analytics, experimentation design, and AI applications within user research.

• Leadership Development: Potential to grow into a lead researcher role, mentor junior researchers, or contribute to defining the strategic direction of the user research function as practices mature.

• Cross-Functional Expertise: Develop a comprehensive understanding of the entire product development lifecycle and gain broader business acumen by working closely with Product, Design, Engineering, Sales, and Customer Success.

• Industry Impact: Contribute to high-impact educational products, gaining satisfaction from directly influencing learning outcomes for students nationwide.

📝 Enhancement Note: The "Senior" title and focus on maturing practices suggest a role with significant autonomy and the potential for substantial impact. Growth opportunities are likely tied to the expansion of the research function and the company's increasing reliance on data-driven product development. Candidates should express interest in building and scaling processes, aligning with the company's growth trajectory.

🌐 Work Environment

Office Type: Fully Remote, with the ability to work from anywhere within the United States. This offers maximum flexibility.

Office Location(s): While the role is remote, the company headquarters are in Washington D.C. (based on location data derived from previous job postings, not explicitly stated in this one). The derived location of "Mäntsälä, Uusimaa, Finland" seems to be an anomaly and should be disregarded in favor of the explicit "Remote (United States)" designation.

Workspace Context:

• Independent Work: The role requires a self-disciplined individual comfortable working autonomously from a home office setup.

• Digital Collaboration Tools: Heavy reliance on virtual collaboration tools (e.g., Slack, Zoom, Google Workspace) for communication, meetings, and project management.

• Data-Intensive Environment: Access to and use of various analytics, research, and data visualization tools will be standard.

• Cross-functional Interaction: Regular engagement with remote teams across different departments, fostering a collaborative but virtual work environment.

Work Schedule: The role is full-time, with an expected 40 hours per week. While remote work often offers flexibility, core working hours may be established to facilitate team collaboration and synchronous communication, especially across different time zones within the US.

📝 Enhancement Note: The fully remote nature of this position is a significant advantage. Candidates should highlight their experience and comfort with remote work dynamics, including effective virtual communication, self-management, and leveraging technology for seamless collaboration. The ability to manage one's own time and maintain productivity in a remote setting is paramount.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter or hiring manager will review applications and resumes, looking for alignment with required skills and experience, particularly in quantitative research and product analytics.

• Hiring Manager Interview: A discussion with the Associate Director, User Research, focusing on your background, research philosophy, quantitative skills, and how you approach product problems.

• Technical/Skills Assessment: This may involve a practical exercise or a deep dive into your portfolio, potentially including a case study presentation or a SQL/data analysis challenge to assess your quantitative capabilities and ability to communicate findings.

• Cross-functional Interviews: Interviews with key stakeholders such as Product Managers, Designers, or Engineers to assess collaboration style, communication effectiveness, and ability to integrate research into the product development workflow.

• Final Interview: Potentially with a senior leader to discuss overall fit, strategic thinking, and long-term contributions to the team and company.

Portfolio Review Tips:

• Quantify Impact: For each project, clearly articulate the problem, your methodology, the key findings, and – most importantly – the measurable impact your research or analysis had on the product or business. Use numbers and metrics wherever possible.

• Showcase Process: Detail your step-by-step approach for quantitative studies, analytics implementation, or A/B test design. Demonstrate how you moved from data collection to actionable insights.

• Highlight Tool Proficiency: Explicitly mention the tools you used (e.g., SQL, Looker, Google Analytics, Excel) and how you leveraged their capabilities to achieve specific outcomes.

• Mixed-Methods Integration: If applicable, showcase projects where you successfully combined quantitative data with qualitative insights to provide a more complete picture.

• Clarity and Conciseness: Present your work clearly and concisely. Use visuals (charts, graphs, dashboards) effectively to support your narrative. Be prepared to walk through your portfolio and answer detailed questions about your contributions.

Challenge Preparation:

• Data Analysis Scenario: Be prepared for a scenario-based question or a take-home assignment that requires you to analyze a dataset, identify insights, and recommend product actions. Practice SQL queries and data interpretation.

• Experiment Design: Be ready to discuss how you would design an A/B test for a specific product feature, including defining hypotheses, success metrics, and potential pitfalls.

• Communication of Insights: Practice articulating complex quantitative findings to a non-technical audience, focusing on the "so what?" and actionable recommendations.

• Tool Expertise: Refresh your knowledge of key analytics and BI tools mentioned in the requirements. Be ready to discuss your experience and proficiency.

📝 Enhancement Note: The emphasis on a quantitative focus means your portfolio should prominently feature projects demonstrating rigorous data analysis, A/B testing, and the use of analytics platforms. Be ready to discuss your process for ensuring data quality and building scalable analytics infrastructure, which is crucial for a role focused on maturing these practices.

🛠 Tools & Technology Stack

Primary Tools:

• Analytics Platforms: Google Analytics, Pendo, Maze, Looker, Microsoft BI, Statsig. Candidates should be proficient in at least one major analytics platform and familiar with others.

• Data Querying: SQL (working proficiency required), Python (a plus). Essential for data extraction and manipulation.

• Spreadsheet Software: Microsoft Excel, Google Sheets for data analysis, manipulation, and reporting.

• Experimentation Tools: Familiarity with A/B testing platforms (e.g., Statsig, Optimizely, VWO - though not explicitly listed, the concept is key).

Analytics & Reporting:

• Dashboarding Tools: Looker, Microsoft BI are specifically mentioned for building and interpreting dashboards and reports.

• Data Visualization: Ability to create clear and compelling visualizations from raw data to communicate insights effectively.

CRM & Automation:

• While not explicitly detailed for this role, familiarity with CRM systems (like Salesforce) and automation platforms may be beneficial for understanding user data flow and cross-functional collaboration within the broader tech stack.

• AI Tools: Mentioned as a way to identify efficiencies, indicating an openness to leveraging AI for research design, reporting, and analysis.

📝 Enhancement Note: Proficiency in SQL and at least one major analytics/BI platform (like Looker or Google Analytics) is non-negotiable. Candidates should highlight their experience with these tools, emphasizing how they've used them to extract insights, build dashboards, and drive product decisions. Familiarity with experimentation platforms and data governance principles will also be highly valued.

👥 Team Culture & Values

Operations Values:

• Data-Driven Impact: A core value is using data and research to make informed decisions that demonstrably improve educational outcomes and user experiences.

• Mission Alignment: A strong commitment to Great Minds' mission of providing high-quality, knowledge-rich content and tools for educators and students.

• Collaboration & Partnership: Fostering strong working relationships across product, design, engineering, and other departments to ensure research is integrated and actionable.

• Continuous Improvement & Innovation: An ongoing effort to mature research practices, scale operations, and leverage new technologies (like AI) to enhance efficiency and effectiveness.

• Usability & Practicality: A focus on developing products and tools that are intuitive, effective, and designed for real-world classroom needs.

Collaboration Style:

• Cross-Functional Integration: Actively embedding research within product development lifecycles, working closely with Product Managers, Designers, and Engineers.

• Knowledge Sharing: Openness to sharing findings and methodologies with other researchers and stakeholders to build a collective understanding and elevate research practices across the organization.

• Data Triangulation: Partnering with non-digital departments to combine insights from various sources, building a holistic view of the customer.

• Supportive and Growth-Oriented: A culture that supports the development of research practices and encourages individuals to grow their skills and contribute to the team's success.

📝 Enhancement Note: Emphasize how your personal values align with Great Minds' mission and their collaborative, data-driven approach. Highlight instances where you've successfully partnered with diverse teams to drive impactful outcomes, demonstrating your ability to thrive in a mission-oriented, collaborative environment.

⚡ Challenges & Growth Opportunities

Challenges:

• Maturing Analytics Practices: As a key responsibility, you'll be instrumental in developing and scaling the digital product analytics function, which can involve defining processes from scratch, ensuring data quality, and driving adoption.

• Integrating Mixed Methods: Effectively blending quantitative findings with qualitative insights to provide a comprehensive, nuanced understanding of user behavior and needs.

• Influencing Without Authority: Driving product decisions and strategy changes based on research insights, requiring strong communication, persuasion, and stakeholder management skills.

• Scaling Research Operations: Building efficient processes for recruitment, data management, and documentation to support a growing product suite and user base.

• Data Privacy in EdTech: Navigating the complexities of data privacy, especially concerning minors, if K-12 user data is involved.

Learning & Development Opportunities:

• Advanced Analytics & Experimentation: Opportunities to deepen expertise in complex quantitative analysis, experimental design, and statistical modeling.

• AI in Research: Exploring and implementing AI tools to enhance research efficiency, analysis, and data insights.

• Product Strategy Contribution: Playing a significant role in shaping the strategic direction of Great Minds' digital products.

• Mentorship and Practice Building: Contributing to the growth and formalization of the user research function within the company.

• Industry Exposure: Working within the EdTech sector, understanding the unique needs and challenges of educators and students.

📝 Enhancement Note: Frame the challenges as opportunities for growth and impact. For example, "Maturing analytics practices" can be presented as a chance to build a robust data infrastructure and establish best practices that will benefit the company long-term. Highlighting your proactive approach to learning and problem-solving will be key.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you used quantitative data to identify a significant user behavior pattern. What was the pattern, what data did you use, and what was the outcome?" (Focus on your process, data sources, and impact.)

• "How would you approach designing an A/B test for a new feature in our [mention a Great Minds product, e.g., Eureka Math platform]? What metrics would you track, and how would you ensure statistical significance?" (Demonstrate your understanding of experimentation design and metrics.)

• "Imagine our product analytics show a sudden drop in user engagement on a key feature. What steps would you take to investigate this issue, and what tools would you use?" (Showcase your problem-solving methodology and analytical toolkit.) Company & Culture Questions:

• "Why are you interested in Great Minds and our mission to improve education?" (Connect your personal values and career goals to the company's mission.)

• "How do you ensure your research findings are effectively communicated and acted upon by product teams?" (Highlight your communication strategies and experience influencing stakeholders.)

• "Describe your experience working in a fully remote environment. How do you maintain productivity and collaboration?" (Emphasize self-management, communication tools, and proactive engagement.) Portfolio Presentation Strategy:

• Structure for Impact: For each case study, clearly outline: Problem -> Your Role -> Methodology (esp. quantitative) -> Key Findings -> Recommendations -> Impact (quantified).

• Data Visualization: Use clear, well-labeled charts and graphs to illustrate your findings. Be prepared to explain what each visualization represents and why it's important.

• Tool Demonstration: If possible, show examples of dashboards you've built or analyses you've performed using specific tools (e.g., SQL queries, Looker dashboards).

• Narrative Flow: Tell a compelling story about how your research led to tangible improvements, focusing on the "why" and "how" behind your actions and their results.

• Concise Explanations: Be prepared to summarize complex projects quickly and dive deeper into specific aspects when asked.

📝 Enhancement Note: For this role, be ready to showcase your quantitative rigor. Prepare to discuss specific data points, statistical concepts, and how you've used SQL and analytics platforms to uncover insights. Your ability to translate technical data into clear, actionable business recommendations for product development will be a key differentiator.

📌 Application Steps

To apply for this Senior User Researcher (Quantitative) position:

• Submit your application through the provided application link on the Great Minds careers portal.

• Tailor your Resume: Highlight specific experiences with digital product analytics, quantitative user research methodologies, SQL, and analytics platforms (Google Analytics, Looker, etc.). Quantify your achievements with metrics wherever possible.

• Craft a Compelling Cover Letter: Clearly articulate your passion for Great Minds' mission, your quantitative research expertise, and why you are a strong fit for maturing their analytics and research practices.

• Prepare Your Portfolio: Select 2-3 strong case studies that showcase your quantitative research skills, A/B testing experience, data analysis capabilities, and ability to drive product decisions. Be ready to present and discuss them in detail.

• Research Great Minds: Understand their products (Eureka Math, Wit & Wisdom, etc.), their mission, and their target audience (educators, students). Consider how your role would contribute to their success and how you might approach research within their context.

⚠️ 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.