Data Analysis Expert - Evaluator

Mercor; New York (NY); Remote; USD 55,000 - 96,000; Part time

Job summary

Mercor is seeking expert Evaluators to review AI-generated outputs such as documents, spreadsheets, and slide decks for accuracy and domain quality. You will apply deep subject-matter expertise to grade these artifacts remotely.

The role is an hourly engagement, requiring 5+ years in data analysis, native English fluency, and fluency with Microsoft Office and Google Workspace (notably Slides). This is a remote, flexible opportunity for skilled evaluators.

Qualifications

• 5+ years of relevant professional experience in Data analysis / quantitative readouts.
• Native or professional fluency in English.
• Highly proficient in Microsoft Office and Google Workspace, especially Slides (Google Slides / PowerPoint).
• Advanced degree (Master's or higher) from a reputable institution.

Responsibilities

• Evaluate AI-generated artifacts against domain-specific quality rubrics.
• Identify factual, aesthetic, and presentation errors.
• Provide clear, structured written feedback.

Skills

Data analysis / readouts

English fluency

Office & Slides proficiency

Education

Master's degree or higher

Tools

Microsoft Office

Google Workspace

Google Slides / PowerPoint

Job description

About the role

We are hiring expert Evaluators in Data analysis / quantitative readouts to review and assess AI-generated work products (documents, spreadsheets, and slide decks) for accuracy, rigor, and domain quality. You will apply deep subject-matter expertise to grade outputs.

This is a remote, hourly engagement.

Requirements (must have)

1. 5+ years of relevant professional experience in Data analysis / quantitative readouts.

2. Native or professional fluency in English.

3. Highly proficient in Microsoft Office and Google Workspace, especially Slides (Google Slides / PowerPoint).

Preferred (nice to have)

• Advanced degree (Master's or higher) from a reputable institution.

What you'll do

• Evaluate AI-generated artifacts against domain-specific quality rubrics.

• Identify factual, aesthetic, and presentation errors.

• Provide clear, structured written feedback.