AfterQueryCoding & software eval
Data Scientist Expert
$115/hr
About this role, in AfterQuery's words
AfterQuery builds the expert evaluation data that frontier AI labs use to measure and improve their models. We're hiring data scientists as contractors to author and solve the analysis problems those evaluations run on, drawn from the work you do every day: experiments, metrics, forecasting and predictive models. This role is for practicing data scientists with hands-on modeling and statistics experience. We're not looking for data engineers, ML engineers or reporting-only analysts. Fully remote and async, with no fixed hours.
What you'll do
Responsibilities
- Author realistic data science problems drawn from your own work: experiments, metrics, forecasting, segmentation and predictive modeling
- Work each problem through to a reference answer, with the reasoning behind every step
- Catch the analysis mistakes that look reasonable but only a practitioner would spot
Candidate background
Required qualifications
- Master's or PhD in statistics, computer science, economics, mathematics or another quantitative field
- 3+ years full time as a data scientist (internships and school don't count)
- Strong SQL and Python or R
- Hands-on statistics: A/B testing, regression, causal inference or predictive modeling
- Able to commit at least 10 hours per week
Preferred qualifications
Show all 3 itemsHide these 3 items in Preferred qualifications
- Experience on a product, growth or marketplace team
- Experience designing and reading out experiments
- Clear written English and comfort explaining an analysis step by step
Quoted from selected sections of AfterQuery's posting. The full posting may state other conditions. Read the full posting
A closer look
More context, when you need it.
Full job descriptionThe original posting, in AfterQuery's words
Posted by AfterQuery, reproduced here so you can judge the role before clicking. Original posting ↗
AfterQuery builds the expert evaluation data that frontier AI labs use to measure and improve their models. We're hiring data scientists as contractors to author and solve the analysis problems those evaluations run on, drawn from the work you do every day: experiments, metrics, forecasting and predictive models. This role is for practicing data scientists with hands-on modeling and statistics experience. We're not looking for data engineers, ML engineers or reporting-only analysts. Fully remote and async, with no fixed hours.
Responsibilities - Author realistic data science problems drawn from your own work: experiments, metrics, forecasting, segmentation and predictive modeling - Work each problem through to a reference answer, with the reasoning behind every step - Catch the analysis mistakes that look reasonable but only a practitioner would spot
Required qualifications - Master's or PhD in statistics, computer science, economics, mathematics or another quantitative field - 3+ years full time as a data scientist (internships and school don't count) - Strong SQL and Python or R - Hands-on statistics: A/B testing, regression, causal inference or predictive modeling - Able to commit at least 10 hours per week
Preferred qualifications - Experience on a product, growth or marketplace team - Experience designing and reading out experiments - Clear written English and comfort explaining an analysis step by step
Why apply - Work stays in your specialty and is judged on analytical judgment, not volume - Set your own hours and scale up or down week to week - Weekly pay via Stripe - Your judgment shapes how the next generation of AI handles data science
Working with AfterQueryPay, getting started and work, from AfterQuery's own pages
What the platform publishes in general. These are not extra terms confirmed for this particular role.
- Getting paid
- Approved work is paid every Friday for the prior week, by Stripe to a bank account, with no fees. Stripe holds the first payout for 7 days. docs.afterquery.com/articles/payments-taxes/payment-setup
- Before your first paid task
- One assessment per expert pool, unpaid and with no retake. Onboarding takes about 10 minutes: legal documents, phone, ID through Persona, and payments. docs.afterquery.com/articles/onboarding/assessments, docs.afterquery.com/articles/onboarding/complete-your-onb...
- How much work
- Projects are assigned by assessment fit as they come up, and higher-rated contributors get priority. docs.afterquery.com/articles/onboarding/assessments, docs.afterquery.com/articles/about/contract-work
- Contract
- Independent contractor. Most contractors register as individuals. docs.afterquery.com/articles/about/contract-work, docs.afterquery.com/articles/onboarding/complete-your-onb...
Read on the pages linked above on 23 Sep 2026. Platforms change these terms, so check the linked page before you rely on one.
How does the pay compare?Across Coding & software eval roles, not this role alone
From our own daily reads of every open listing on the platforms we follow, not from AfterQuery's posting. How we count.
Pay across the field: Coding & software eval
Across 393 roles in this field with a stated hourly rate in US dollars, on 14 platforms, the middle half pays $65 to $120 an hour at the top of the range, and the median is $95. This role's top rate, $115, is in the middle half. Of the 141 distinct rates we count, 96 are lower and 44 are higher.
| Platform | Roles | Top of range, per hour |
|---|---|---|
| Alignerr | 137 | $50 to $400 · median $100 |
| micro1 | 46 | $35 to $350 · median $110 |
| Handshake AI | 43 | $47 to $125 · median $80 |
| Meridial (Invisible) | 34 | $22 to $150 · median $60 |
| Mercor | 33 | $60 to $200 · median $105 |
Sources and listing historyWhere this information comes from
This listing's history
- First seen here on 7 Oct 2026, and still on AfterQuery's list when we last read it on 12 Oct 2026.
- The listed pay has not changed since then.
- Posted by AfterQuery
- First seen by AIPayList
- Last seen live
- Listing ID
- 1791401369308
Pay as the source states it: “$115/hr”.
Platforms sometimes change a rate after posting. Every listing here is re-read at least once a day and corrected when its source moves, so a difference you see on the platform is usually a change made since the last read. How freshness works.
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