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Salary: USD 196,000 - 230,000 / annual
Notion is seeking an experienced User Researcher to drive growth-related product decisions by delivering insights that fuel AI experiences. This role uniquely blends traditional growth research—adoption, monetization, pricing and packaging—with fast-evolving AI features like Notion Agent and Chat that permeate onboarding and workspace creation experiences.
You will design and execute mixed-methods research studies (qualitative and quantitative) including interviews, concept testing, prototype/usability testing, diary studies, surveys, and advanced pricing studies. Your work will evaluate how people discover, trust, and derive value from AI features, identifying barriers to adoption and willingness to pay. You'll leverage AI tooling to scale your research process, reporting, and overall impact.
Key responsibilities include delivering actionable insights that enable deep customer understanding, identifying business opportunities, and driving strategic decision-making across the organization. You'll work with complex user journeys and growth engines, connecting research findings directly to business outcomes and revenue implications.
Required qualifications: 5+ years of UX research in industry, AI fluency with hands-on product experience, systems thinking to understand complex user journeys, business mindedness connecting research to strategy, data fluency with experimentation and behavioral analytics, pragmatism in fast-moving environments, and strong communication skills with creative insight-sharing approaches.
Nice-to-haves include experience researching AI-enabled and agentic products, B2B research expertise, familiarity with AI research tools (Outset, Listen Labs, Dovetail), advanced degrees in HCI/Psychology/Behavioral Economics, and experience communicating with executive stakeholders.
The role is based in either San Francisco or New York City with hybrid work on Mondays, Tuesdays, and Thursdays (Anchor Days). Notion is building the collaborative AI workspace where teams and agents think together, enabling faster, clearer, less fragmented work.
