UX Researcher Expert
Ethos • Remote
Education
Not stated
Type
Hourly
Pay Rate
$70/hr
Listed
33d ago
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From the Ethos listing
About This Opportunity
We're working with a leading foundational AI lab to find experienced UX researchers who can help train their latest language model on professional document, spreadsheet, and slide deck tasks.
We're looking for UX researchers with 4+ years in customer or user research, feedback synthesis, or product discovery to create, evaluate, and refine AI-generated documents, spreadsheets, and slide decks across core workflows: moderated usability test findings decks, customer interview synthesis and thematic coding summaries, survey instrument design and analysis writeups, discussion guides and screener criteria for research studies, research repository tagging and insight briefs, and journey map documents translating findings into product recommendations.
Compensation: $70/hour
Commitment: Flexible, 5-20 hours per week (or more if desired)
Location: Fully remote, work on your own schedule
Start date: ASAP
Qualifications
- 4+ years conducting customer or user research (interviews, usability testing, surveys) with ownership of the full study lifecycle from discussion guide to insight synthesis
- Fluency with thematic coding methods, survey design/statistics, and translating raw research data into usability test findings decks and journey map documents
- Expert-level document, spreadsheet, and slide craftsmanship, with excellent written communication and attention to detail
About Ethos
Ethos is a new expert network built by a McKinsey/SoftBank/DeepMind team and backed by world-leading investors like General Catalyst. We connect experts with investors and consultancies for paid expert calls, speaking engagements, and advisory opportunities.
How long hiring takes
Across the AI training platforms we refer candidates to, the median gap between referral and hire is about 30 days. It varies by platform and role, so treat it as a rough guide for this one.
Interview Prep
Sample questions for a UX Researcher role, written in-house to help you prepare.
How do you decide whether a research question calls for generative research, exploring an open problem, or evaluative research, testing a specific solution?
I look at whether there's already a concrete design or concept to react to. If there isn't, the work is generative: open-ended interviews or diary studies aimed at understanding the problem space before any solution exists. Once there's something concrete to test, like a prototype or an existing flow, the work shifts to evaluative methods that measure how well that specific solution performs against real tasks.
How do you decide between quantitative and qualitative methods for a given research question, or when to combine both?
Qualitative methods answer why something happens and give me the context behind a behavior, which is what I need early or when the mechanism itself is unclear. Quantitative methods tell me how common a pattern is across a larger group, which matters once I already have a hypothesis and need to know its scale. On higher-stakes questions I run both: a qualitative round to surface the real issues, then a survey or analytics check to confirm how widespread they are.
What's your process for running a moderated usability test, and what do you capture beyond whether the participant completed the task?
I use a think-aloud protocol so I can hear the participant's reasoning as they move through the flow, since the reasoning matters as much as whether they reach the end. Beyond task success and time on task, I note every point of hesitation, backtracking, or misread label, since that's usually where the real design problem lives even in an otherwise successful session. I stay careful not to prompt or explain during the task, since even a small hint changes what the session measures.
How do you approach thematic coding when synthesizing findings from a large batch of interview transcripts?
I read through a handful of transcripts first without coding anything, to let recurring themes surface naturally rather than forcing the data into categories I expected going in. Then I build a codebook from what showed up and apply it consistently across the rest of the batch, revising it if a later transcript surfaces something the early pass missed.
Why this role
$70/hr for UX Researcher Expert work puts your Design expertise on the same footing as an AI lab's own research staff, without the overhead of running a consulting practice around it.
Talent pool
We're light on Design candidates
We've matched 30 people with a Design background against 397 Design listings we've tracked, so most go out without one. Set up a profile and we'll consider you for a role like this one.
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Common questions
Is Ethos regular AI training work like rating chatbot responses?
No. Ethos is an expert network, not a task queue. AI labs, investment funds, and Fortune 500s pay to access your specific domain knowledge (deal analysis, clinical reasoning, legal logic, financial modeling) through three formats: multi-week consulting engagements, 30-60 minute advisory calls, and targeted research surveys.
Do I need to keep applying for projects on Ethos?
No. Once your profile is live, Ethos's algorithm matches you to inbound opportunities based on your career history, so companies find you instead of you hunting for listings. Your Expert Score rises with each completed engagement and unlocks higher-value work over time. Ethos already works with 25+ private equity firms, hedge funds, and consultancies, so the deal flow behind this is real.
What does asynchronous AI training work mean in practice?
No set hours, no check-ins, no meetings. You log in when you want, pick up an available task, complete it, and submit; nobody is waiting on you in real time. That's different from remote employment, where you're expected online during business hours. The tradeoff: you're competing with others for available tasks, so an empty queue means there's simply nothing to do until more work is released.
Do task-based AI training roles require an interview?
Most skip a live interview entirely and gate access through an automated assessment or qualification task instead. Where we've confirmed the specific requirement for this listing, it's called out above in What We Know About This Role.
What does Design work look like for an UX Researcher Expert?
Tasks here are scoped to Design, not generic labeling. As an UX Researcher Expert, expect to draw on real domain judgment (evaluating outputs, correcting errors, or providing expert reasoning specific to Design) rather than following a one-size-fits-all rubric. If you don't have hands-on Design background, this is likely not the right listing to start with.
What specific skills does this listing call for?
Expert is named directly in the listing. If you don't have hands-on experience with this, expect the screening process to test for it directly rather than accepting adjacent experience as a substitute.
How much does this specific role pay?
This listing is posted at $70/hr, an hourly rate. Pay can change between when we last checked the listing and when you apply, so confirm the current number on the platform's own application page before committing time.
What happens when I click Apply on this listing?
You'll be taken to Ethos's external site to complete your application there. This listing links through a referral, but the process is identical to applying directly; the link just routes you correctly. Create an account on their site and follow their onboarding steps.
Who built Ethos and is it legitimate?
Yes, it's legitimate and well-funded: Ethos raised $3.5M from General Catalyst and was co-founded by Daniel Mankowitz (Google DeepMind research scientist and lead author of AlphaDev) and James Lo (McKinsey, SoftBank Vision Fund). Over 17,000 experts have signed up, and it's actively working with 25+ PE firms, hedge funds, and consultancies. The referral link on this page is an affiliate link; it doesn't affect your pay or opportunities.