This is a standing listing for analysts and data practitioners who want AI training and evaluation work, not a specific job opening. It stays open whether or not a matching project is running this week.

New projects start on short notice, so instead of posting and pulling a listing each time, we keep one open per field and draw from it when one begins.

We match data practitioners in the network to projects like:

What this covers.

This pool spans data analysis, including:

• Business intelligence.
• Data engineering.
• Statistics
• Machine learning.

Where you trained matters less than whether you have shipped analyses someone made a decision on.

How it works.

Apply here with your resume and confirm where you work from, then take a short AI interview, about 20 minutes total.

We verify your background and add you to the data analysis pool.

When a project needs your specialty, we invite matching people from the pool to that specific listing. It names the rate, the hours, and the client, and any hiring decision is made there.

What to expect.

This listing does not accept or reject candidates, so you will not get a decision on it. We reach out when a project matches your background. Depending on what our clients are running, that can be within a week or several months.

Finishing the domain expert interview and joining every network you qualify for both improve your odds of being matched. You only need to sign up once to be eligible across all of them.

Contract and Payment Terms.

• You will be engaged as an independent contractor.
• This is a fully remote role that can be completed on your own schedule.
• Projects can be extended, shortened, or concluded early depending on needs and performance.
• Your work at Mercor will not involve access to confidential or proprietary information from any employer, client, or institution.

• Writing an analysis problem from work you actually shipped, with the data, the question, and the constraint, plus the reference answer a model's attempt gets graded against.
• Grading model-written analysis and pipelines: whether the query answers the question that was asked, whether the join fans out, whether the metric means what the model says it means.
• Flagging where a model produces a technically valid result that would mislead a decision-maker, given selection effects, leakage, or a metric that does not track the outcome.

Work arrangement: Fully remote

• Please note: We are unable to support H1-B or STEM OPT candidates at this time.

• Payments are weekly on Stripe or Wise based on services rendered.