Tools, Frameworks & Implementation Proficiency Topics
Practical proficiency with industry-standard tools and frameworks including project management (Jira, Azure DevOps), productivity tools (Excel, spreadsheet analysis), development tools and environments, and framework setup. Focuses on hands-on tool expertise, configuration, best practices, and optimization rather than conceptual knowledge. Complements technical categories by addressing implementation tooling.
Research Tools and Platforms Proficiency
Demonstrate proficiency with research tools and platforms commonly used at FAANG companies: user research platforms (Validately, UserTesting, Respondent), analytics tools (Google Analytics, Mixpanel, Amplitude), survey tools (Qualtrics, SurveyMonkey), and analysis software (NVivo, ATLAS.ti, or custom analysis approaches). Be prepared to discuss tool selection based on research needs.
Research and Product Analytics Tools
Proficiency with user experience research and product analytics platforms used to generate qualitative and quantitative insights. This includes hands on use of remote and moderated research tools such as UserTesting Maze and Optimal Workshop and prototyping or usability tools such as Figma; and analytics platforms such as Google Analytics Amplitude and Mixpanel for event tracking funnel analysis cohort analysis retention analysis and experiment evaluation. Candidates should be able to design studies recruit participants select metrics instrument events interpret mixed methods results create dashboards and translate findings into product improvements. Include knowledge of experiment design A B testing basics data quality and how to combine qualitative observations with quantitative signals.
Research Platform and Tools Architecture
Selecting and integrating research platforms and tools to support qualitative and quantitative research workflows. Topics include evaluation of survey platforms, usability testing tools, qualitative analysis systems, participant management, data storage and security for research data, and integration points with analytics and reporting systems. Candidates should demonstrate the ability to match tools to research goals, consider cost and complexity, and design architectures that preserve data privacy and support analysis.
Research Infrastructure and Tools
Knowledge of the tooling and infrastructure needed to run research at scale. Topics include participant recruitment and panel management platforms, survey and qualitative tooling, video capture and transcription, analytics and dashboarding, research repositories and knowledge management, integration with product telemetry and analytics stacks, vendor selection and management, budgeting and contracting for research, and operational practices to support collaboration and dissemination.
Technical Skills and Tools
A concise but comprehensive presentation of a candidate's core technical competencies, tool familiarity, and practical proficiency. Topics to cover include programming languages and skill levels, frameworks and libraries, development tools and debuggers, relational and non relational databases, cloud platforms, containerization and orchestration, continuous integration and continuous deployment practices, business intelligence and analytics tools, data analysis libraries and machine learning toolkits, embedded systems and microcontroller experience, and any domain specific tooling. Candidates should communicate both breadth and depth: identify primary strengths, describe representative tasks they can perform independently, and call out areas of emerging competence. Provide brief concrete examples of projects or analyses where specific tools and technologies were applied and quantify outcomes or impact when possible, while avoiding long project storytelling. Prepare a two to three minute verbal summary that links skills and tools to concrete outcomes, and be ready for follow up probes about technical decisions, trade offs, and how tools were used to deliver results.