Senior User Researcher (Quantitative)
About the role
The Senior User Researcher is a mixed methods researcher with a quantitative focus, who matures digital user research practices for an education curriculum company. As an individual contributor, they play a key role in establishing and making usable digital platform analytics, as well as contributing to digital platform strategy through studies and supporting research operations. Reporting to the Associate Director, User Research, this role focuses on understanding how users interact with products at scale and translating data into learning that informs product decisions and strategy. This role is ideal for a researcher with a deep passion for analytics and mixed methods research, and an interest in growing experimentation practices that combine quantitative and qualitative approaches within a product discovery environment. They thrive working cross-functionally, partnering closely with both the digital partners in Product, Design, and Engineering as well as non-digital partners in Sales and Customer Success. They are comfortable and eager to move between product strategy and the hands-on detailed work to keep research running smoothly. At Great Minds, we create high-quality, knowledge-building materials that deepen understanding and ignite a lifelong love for learning. We provide educators with the tools they need to help every student reach their full potential. We believe that every child is capable of greatness.
Responsibilities
- Digital Product Analytics: Design and support implementation of advanced analytics tooling, including coordinating closely with engineers, identifying naming taxonomies, and identifying data governance approaches; support self-service enablement, including training team members on usage, creating documentation, creating dashboards.
- Research & Analysis: Design and execute mixed-methods research using data from e.g., product analytics, surveys, usage data, 1:1 interview, observations; analyze online user behavior to identify patterns, trends, and opportunities for improvement; monitor and improve data quality, including coordinating with engineers and refining data taxonomies; design and analyze A/B tests and experiments to inform product decisions; build and interpret dashboards and reports using tools such as Looker, Microsoft BI, Google Analytics; leverage AI to identify efficiencies for study design, reporting, analysis and data visibility.
- Product Discovery: Support hypothesis-driven discovery and early experimentation; contribute to experiment design and analysis as experimentation practices mature; contribute to large-scale foundational studies to inform product strategy.
- Communication of Insights & Findings: Translate complex data into clear, compelling narratives that drive product decisions; present findings to Product, Design, and leadership audiences.
- Cross-Functional Collaboration: Build strong working relationships with Product Managers, Designers, and Engineers to embed research into the digital product development lifecycle; work closely and collaboratively with other researchers to mature research practices and complete studies to show impact of data-informed decision making; partner with non-digital departments to triangulate insights, build confidence in research and decision-making that follows.
- Research Operations: Support recruitment needs of product workstreams, including growing our internal participant panel; develop efficiencies to scale quality research practices, leveraging AI or automation where useful; build documentation practices for product workstreams to enhance research repository; contribute hands-on to operational needs as the team scales its practices.
Requirements
- 3+ years of experience (5+ years preferred) working with digital product analytics or quantitative user research for SaaS or web-based software products.
- Experience with analytics platforms, A/B testing and analysis tools such as Google Analytics, Pendo, Maze, Looker, Statsig, Microsoft BI, Excel, and Google Sheets.
- Working proficiency in SQL, with Python a plus, for querying and analyzing data across multiple sources.
- Demonstrated ability to collaborate effectively across Product, Design, Engineering, and Data teams, and to influence decisions without direct authority.
- Demonstrated ability to work independently when driving research studies while staying aligned with cross-functional partners.
- K–12 or education experience is a plus, not required.
- Experience with data privacy considerations for vulnerable populations, such as minors, is a plus, not required.