Business Intelligence / Data Analyst Expert

Ethos

United States

Remote

USD 83,000 - 138,000

Part time

40 hours ago
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Benefits offered by this job

Fully remote

Job summary

Ethos is seeking a Business Intelligence/Data Analyst Expert to contribute to data-driven decision-making on a flexible, remote schedule. Candidates should bring hands-on SQL experience and proficiency with BI or dashboard tools, plus a demonstrated ability to translate data into actionable reports for stakeholders.

Strong written communication and meticulous attention to detail are essential. The role offers up to 20 hours per week at $80/hour, with remote work that fits your own schedule and

Qualifications

  • Hands-on experience with SQL and BI or dashboard tools.
  • Track record of turning data into reports stakeholders act on.
  • Excellent written communication and attention to detail.

Job description

Compensation

$80/hour
Commitment:
Flexible, up to 20 hours per week (up to $1,600/week)
Location:
Fully remote, work on your own schedule

Qualifications

Hands-on experience with SQL and BI or dashboard tools
Track record of turning data into reports stakeholders act on
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 platforms we work with, people typically hear back about a hire within

about

30 days
of being referred.
Some are quicker, some take longer.
Within 2 weeks
~25%
Within 6 weeks
~65%
Within 3 months
~80%
Business Intelligence Analyst Interview Prep
Practice questions for Business Intelligence Analyst interviews in general. They are not taken from this listing, but they cover what interviewers in this field tend to ask.
How do you decide when a metric belongs in a dashboard versus a one-off analysis?
A dashboard metric needs to be something stakeholders check repeatedly to make ongoing decisions, and it needs a stable, well-understood definition. If a metric requires a fresh explanation every time someone looks at it, or the underlying question only comes up occasionally, it's better as an ad hoc analysis than a permanent dashboard tile that adds clutter without recurring value.
Explain how you would write a SQL query to find month-over-month percentage change in a KPI using window functions.
I'd aggregate the KPI by month first, then use the LAG window function partitioned appropriately and ordered by month to pull the prior month's value into the same row. From there the percentage change is a straightforward calculation between the current and prior value, which avoids the self-join that a lot of analysts default to for this kind of comparison.
How do you approach designing a dimensional model for a warehouse that needs to support multiple, sometimes conflicting, reporting needs?
I start from the grain of the fact table, since getting that wrong makes everything downstream harder to reconcile. Conflicting reporting needs usually mean different teams want different aggregation levels, which is solved by keeping the fact table at the most granular useful level and letting each report aggregate up from there, rather than pre-aggregating and locking in one team's view.
What's your process for validating that a new dashboard's numbers are correct before sharing it with stakeholders?
I reconcile the dashboard total against a known source, often a manually run query or an existing trusted report, for at least a few time periods before publishing. I also sanity-check edge cases like the most recent partial period and any known one-off events, since those are the spots where a dashboard is most likely to show a misleading number.
See all 10 Business Intelligence Analyst interview questions â
Why this role
This Business Intelligence / Data Analyst Expert role pays $80/hr for your Software Engineering judgment directly, without requiring case files, client meetings, or firm overhead to get there.
Skills and categories
Explore other opportunities in related specializations:
Software Engineering
No Degree Required
Software Engineering & Coding
Business & Strategy
Expert
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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 Software Engineering work look like for a Business Intelligence / Data Analyst Expert?
Tasks here are scoped to Software Engineering, not generic labeling. As a Business Intelligence / 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 $80/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.

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