Data Science Expert - AI Evaluation

Mercor; Toronto; On-site; CAD 120,000 - 170,000; Full time

Job summary

Mercor, partnering with a leading AI research organization, seeks experienced data scientists to help define what excellent work looks like by designing task-specific grading criteria and scoring completed samples with detailed written justifications.

The role emphasizes rigorous evaluation, reproducible scoring, and collaboration with senior reviewers to calibrate judgments across AI training, evaluation, and human-data projects.

Qualifications

• 5+ years of professional data science experience in industry.
• Experience 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 presenting findings to executives.
• Exceptionally strong written communication.
• Detail-oriented with the ability to be calibrated against peers.
• Prior experience with AI training, evaluation, or human-data projects is a strong plus.

Responsibilities

• Design precise, task-specific grading criteria for real-world data science deliverables (analyses, models, dashboards, experiment readouts, and written recommendations).
• Score AI-generated and human work samples against those criteria, with detailed written justifications for every score.
• Apply consistent, evidence-based judgment so that scores are reproducible and defensible.
• Incorporate structured feedback from senior reviewers and iterate quickly on your work.

Skills

Data science experience

Experiment design

Written communication

Executive stakeholder communication

Attention to detail

AI training/evaluation experience

Tools

SQL

Python

Job description

1. Role Overview

Mercor is partnering with a leading AI research organization to engage experienced data scientists for a project focused on evaluating how well AI systems perform real-world data science work. Rather than producing deliverables yourself, you will define what excellent work looks like: designing task-specific grading criteria and scoring completed work samples with rigorous, well-reasoned written justifications.

2. Key Responsibilities

• Design precise, task-specific grading criteria for real-world data science deliverables (analyses, models, dashboards, experiment readouts, and written recommendations)
• Score AI-generated and human work samples against those criteria, with detailed written justifications for every score
• Apply consistent, evidence-based judgment so that scores are reproducible and defensible
• Incorporate structured feedback from senior reviewers and iterate quickly on your work

3. Ideal Qualifications

• 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 and 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
• Prior experience with AI training, evaluation, or human-data projects is a strong plus

4. Application Process

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