Data Science Evaluation Specialist

Mercor; New York (NY); On-site; USD 120,000 - 160,000; 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 scoring completed work samples with rigorous, well-reasoned written justifications.

In this role, you will design precise grading criteria, score both AI-generated and human work samples, and apply consistent,

Qualifications

• 5+ years of professional data science experience in industry.
• Experience in business operations, product, or growth data science at top tech companies.
• Strong expertise in experiment design, A/B testing, metrics, SQL/Python, and executive storytelling.
• Exceptional written communication skills.
• Attention to detail and consistent judgment review.
• Experience with AI training or human-data projects is a plus.

Responsibilities

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

Skills

5+ years data science experience

Business/Operations data science

Experiment design & A/B testing

SQL

Python

Written communication

Attention to detail

AI training/evaluation

Job description

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 scoring completed work samples with rigorous, well-reasoned written justifications.

In this role, you will design precise grading criteria, score both AI-generated and human work samples, and apply consistent,