Description review

Data Science Expert - Fully Remote | Upto $170/hr

mercor · United Kingdom · back to the listing

HR standards

79/100

solid

Title ↔ description

53/100

needs work

Reads as

Unclear

no confident match

What this role officially is

data scientist — ESCO, the EU occupation classification

Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.

Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist

How others title the same work

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What the listing never says

  • No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency

The listing, marked up

Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: Data Science Expert
Type:Contract
Compensation:$120–$170/hour
Location:Remote

Role Responsibilities

• Design precise, task-specific grading criteria for real-world data science deliverables, including analyses, models, dashboards, and experiment readouts.

• Score AI-generated and human work samples against established criteria with detailed, well-reasoned written justifications.

• Apply consistent, evidence-based judgment to ensure scores are reproducible and defensible.

• Incorporate structured feedback from senior reviewers and iterate quickly on your work.

• Collaborate with AI research teams to improve training data quality and downstream performance.

Qualifications

Must-Have

• 5+ years of professional data science experience in industry.

• Background in business operations, product, or growth data science at top-tier technology companies.

• Deep fluency in experiment design, A/B testing, metric definition, SQL/Python analysis, and communicating findings to executive stakeholders.

• Exceptionally strong written communication.

• Detail-oriented, consistent, and comfortable having your judgment reviewed and calibrated against peers.

Preferred

• Prior experience with AI training, evaluation, or human-data projects.

Application Process (Takes 20–30 mins to complete)

• Submit your resume or relevant technical background to get started.

• Qualified applicants may be asked to complete a brief technical assessment or submit additional information.

Resources & Support

• For details about the interview process and platform information, please check:

• For any help or support, reach out to:

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

Originally posted on Himalayas

How this was produced

Highlights are found by rule, not by a model: each one is a phrase matched at a known position, and every note is a template we wrote. The two scores come from a typed-decision model (Jev) that reads the listing against the official role definition and real listings for the same role, and returns probabilities rather than prose — it never writes any of the words on this page, and never chooses what to highlight.

Deterministic penalty applied to the HR score: 4 points (from 83 before penalties). Reviewed 21 Sep 2026.