Data Science Expert - Evaluation Specialist - AI Trainer

Obsidian; Philadelphia (Philadelphia County); On-site; USD 120,000 - 190,000; Full time

Job summary

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. You will define what excellent work looks like, designing task-specific grading criteria and providing rigorous written justifications for scores.

The ideal candidate has 5+ years in industry data science, with strong experiment design, SQL/Python analysis, and the ability to communicate findings to

Qualifications

• 5+ years of professional data science experience in industry.
• Experience in business operations, product, or growth data science at top-tier tech companies.
• Deep fluency in experiment design and A/B testing, metric definition, SQL/Python analysis, and communicating findings to executives.
• Exceptionally strong written communication.
• Detail-oriented and comfortable with peer calibration.
• Prior AI training/evaluation experience is a strong plus.

Responsibilities

• Design precise, task-specific grading criteria for real-world data science deliverables.
• Score AI-generated and human work samples against criteria with detailed written justifications.
• Apply consistent, evidence-based judgment so scores are reproducible and defensible.
• Incorporate structured feedback from senior reviewers and iterate quickly.

Skills

Data science experience

Experiment design

A/B testing

SQL

Python

Written communication

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