Data Analyst Expert
Ethos • Remote
Education
Not stated
Type
Hourly
Pay Rate
$55–$85/hr
Listed
66d ago
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From the Ethos listing
This Data Analyst opening pays $55 to $85 an hour depending on experience and looks for 3+ years of hands-on SQL and BI/dashboard work. The evaluation task is judging AI-generated queries, visualizations, and analytical reports for whether they'd hold up in front of a stakeholder, beyond the numbers simply looking plausible. Ethos is filling it steadily through referrals, and it's one of the more accessible entry points into their analyst-track work.
Requirements
- Must be eligible to work in Remote
- Fluent proficiency in English (Written & Verbal)
- Reliable high-speed internet connection
- Bachelor's degree or equivalent professional experience
- Demonstrated expertise in Software Engineering
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 Data Analyst role, written in-house to help you prepare.
What's your process for cleaning a dataset before starting analysis?
I start by profiling the data for missing values, duplicates, and outliers, then decide case by case whether to impute, drop, or flag issues based on how they'd affect the specific analysis. I document every transformation so the cleaning process is reproducible and reviewable, not just a black box.
How do you decide which statistical test is appropriate for comparing two groups?
I check the distribution of the data and whether the groups are independent or paired first, since that determines whether a t-test, a non-parametric alternative like the Mann-Whitney U test, or a paired test is appropriate. Choosing a test based on convention rather than the data's actual properties leads to unreliable conclusions.
What makes a data visualization misleading, even if the underlying numbers are correct?
Common issues include truncated axes that exaggerate differences, using pie charts for data with too many categories to compare visually, or choosing a chart type that implies a trend the data doesn't actually support. I try to match the chart type to the specific comparison I want the viewer to make.
How do you handle outliers in a dataset when you're not sure if they represent errors or real extreme values?
I investigate the source of the outlier before deciding how to handle it, since a data entry error should be corrected or removed, while a genuine extreme value, like a real high-value transaction, should usually stay in the dataset. Removing outliers automatically without checking their origin risks losing real signal.
Why this role
AI labs pay $55–$85/hr for a Data Analyst Expert because getting Software Engineering nuance wrong in a training set is expensive to fix later. That's what this rate is pricing in.
Skills and categories
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Common questions
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.
How and when does Ethos pay experts?
Within 30 days of invoice submission after a project closes. That net-30 schedule is standard for enterprise expert networks, but it's slower than the weekly payouts some AI training platforms offer, so plan your cash flow around it.
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 task-based AI training work look like?
Practical, hands-on data work: recording short videos, categorizing images, rating text responses, or analyzing data. Tasks are designed to be short and distinct, typically 5 to 60 minutes each.
What does Software Engineering work look like for a Data Analyst Expert?
Tasks here are scoped to Software Engineering, not generic labeling. As a Data Analyst Expert, expect to draw on real domain judgment (evaluating outputs, correcting errors, or providing expert reasoning specific to Software Engineering) rather than following a one-size-fits-all rubric. If you don't have hands-on Software Engineering 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 $55–$85/hr, an hourly rate. The range reflects experience level and negotiated terms, not a placeholder, so where you land in it depends on your background and the assessment. 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.