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Head of Business Intelligence Expert

$80 per hour
Temporary

Pay

$80/hr
The rate in the listing.
?
From the Ethos listing, checked Nov 13.
Listed
Today
Checked
Nov 13
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How Ethos hiring works
Your application is a 10-minute call.
Ethos's AI interviewer asks about your career, then matches you to projects like Head of Business Intelligence. Keep your CV open and walk through the roles and skills that fit this work.
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About this role
From the Ethos listing
About This Opportunity
We're working with a leading foundational AI lab to find experienced heads of business intelligence who can help train their latest language model on professional document, spreadsheet, and slide deck tasks.
We're looking for heads of business intelligence with 4+ years building dashboards, reporting pipelines, and data-driven business narratives to create, evaluate, and refine AI-generated documents, spreadsheets, and slide decks across core workflows: executive KPI dashboards, monthly business performance decks, ad hoc SQL data pulls, data quality and validation checklists, metric definition glossaries, and self-serve reporting templates for stakeholders.

Compensation

$80/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 building and maintaining BI dashboards, KPI reporting, and self-serve analytics for business stakeholders
Fluency in SQL and at least one BI/visualization tool with a proven track record of turning raw data into clear, decision-ready business narratives
Expert-level document, spreadsheet, and slide craftsmanship, with excellent written communication and attention to detail
How long hiring takes
On the platforms we refer people to, half of hires came within

about

25 days
of applying.
Time from applying to hire:
Under 2 weeks
~30%
2 weeks to 6 weeks
~40%
6 weeks to 3 months
~15%
Over 3 months
~15%
Prepare for the Ethos call
Ethos's AI interviewer asks about your Business Intelligence Analyst background. These are our own practice questions for that work, not Ethos's.
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 →
Skills and categories
More jobs in these fields:
Generalist
No Degree Required
Business & Strategy
Expert
AI Training
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Common questions
Is Ethos regular AI training work like rating chatbot responses?
No. Ethos is an expert network. AI labs, investment funds and large companies pay for your domain knowledge (deal analysis, clinical reasoning, legal logic, financial modeling) in three formats: multi-week consulting engagements, 30 to 60 minute advisory calls, and research surveys. Listings like this one are the AI-lab engagements, where you write or review expert material for a model.
Do I need to keep applying for projects on Ethos?
No. When your profile is live, Ethos matches you to new projects from your career history, so companies find you. Each finished project raises your Expert Score, which brings you better-paid work.
How many hours a week is this Head of Business Intelligence work?
Between 5 and 20 hours a week. At $80/hr that is $400 to $1,600 a week. You set your own hours.
What experience does this Head of Business Intelligence listing ask for?
The listing asks for 4+ years building and maintaining BI dashboards, KPI reporting, and self-serve analytics for business stakeholders; fluency in SQL and at least one BI/visualization tool with a proven track record of turning raw data into clear, decision-ready business narratives; and expert-level document, spreadsheet, and slide craftsmanship, with excellent written communication and attention to detail. Ethos's interviewer builds your profile from your CV, so have the roles that show this ready to talk through.
How much does this specific role pay?
This listing is posted at $80/hr, an hourly rate. Pay can change after we check the listing, so confirm the rate on the platform's application page.
What happens when I click Apply on this listing?
The link opens Ethos's sign-up. There is no form for this listing: Ethos's AI interviewer asks about your career in a 5 to 15 minute call, builds your profile from it, and then matches you to projects like this one. Keep your CV open and cover the experience the Qualifications above ask for.
Who built Ethos and is it legitimate?
Yes. Ethos was founded in London in 2024 by James Lo (McKinsey, SoftBank Vision Fund) and Daniel Mankowitz (Google DeepMind research scientist and lead author of AlphaDev). It raised a $22.75M Series A led by a16z in May 2026, with General Catalyst and XTX Markets participating, and works with AI labs, private equity firms, hedge funds and consultancies. The link on this page is an affiliate link; it doesn't affect your pay or the projects you're offered.

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