Design and execute end-to-end mixed-methods studies combining qualitative methods (in-depth interviews, workflow observations, usability studies, concept evaluations) with quantitative methods (surveys, telemetry, large-scale behavioral logs). Define, instrument, and track user-centered key performance indicators and product health indicators, triangulating qualitative workflow pain points with quantitative impact attribution across AI data pipelines.
Build and use agent-assisted pipelines, synthesis workflows, and analysis scripts to pair unstructured qualitative feedback with operational and telemetry logs. Investigate developer and data-practitioner mental models alongside system performance signals to diagnose and reduce user friction, efficiency losses, and cognitive load. Partner with Product Managers, Engineers, UX Designers, Data Scientists, and ML researchers to translate mixed-methods evidence into product direction.
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