Responsibilities

• Set the research agenda for a product area where the strategic questions are still fuzzy. Define what we need to learn, in what order, and why—then go learn it. Don't wait to be asked
• Design and run mixed-methods research at whatever fidelity the moment calls for. Some of it will be careful, foundational work the team references for a year. Some of it will be a finding you ship the same day the question came up
• Keep product teams close to users in a rigorous way—building the channels, cadence, and evidence base that make user reality hard to ignore
• Get hands-on with product data. Pull your own samples, build your own dashboards, instrument what's missing
• Prototype when prototyping is the fastest path to an answer—a research tool, a survey pipeline, a scrappy version of a feature to put in front of users
• Deeply leverage AI in how you work—using Claude to make yourself dramatically more efficient at analysis, synthesis, tooling, and everything in between
• Use what you study. Dogfood our products hard enough to develop your own informed opinions, and bring that texture into your research
• Anticipate where the product is heading before anyone asks. Show up with the user understanding the team is about to need
• Turn what you learn into recommendations confident enough to redirect a roadmap—including recommending we kill something that isn't working
• Build durable understanding, not just findings. The goal is that PMs, designers, and engineers internalize the user mental model well enough to make good calls when you're not in the room
• Develop new research methods when the existing playbook doesn't fit—particularly methods that use AI to do things that weren't possible before

Qualifications

• Industry UX research experience, including ownership of research strategy for a product or product area
• Track record of research that shifted product direction at the strategy level, not just the feature level
• Deep mixed-methods expertise—qualitative and quantitative
• Enough data fluency to use Claude to work directly with our data warehouse—pulling your own samples, writing your own queries, running your own analyses
• Demonstrated technical range: you've built research tooling, prototyped, scripted analyses, or otherwise shown you can keep up with very technical teams without translation overhead
• Advanced, hands-on use of AI in your own research workflow—you're already taking full advantage of its capabilities to enhance how you work
• Experience embedding with engineering-led product teams that ship fast, and earning influence in that environment
• Excellent storytelling, calibrated to audience. You can discuss a finding with an exec as effectively as with an engineer

The annual compensation range for this role is listed below. 

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary:

$305,000 - $385,000 USD

Logistics

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.