AI Evaluation Architect for Data Science

Mercor; New York (NY); On-site; USD 140,000 - 180,000; Full time

Job summary

Mercor seeks experienced data scientists to design task-specific grading criteria for real-world deliverables and to score both AI-generated and human work with detailed justifications. You will ensure reproducible, defensible scoring through evidence-based judgment and rapid iteration with senior reviewers.

Ideal candidates have 5+ years in industry data science, plus deep fluency in experiment design, A/B testing, and communicating findings to executives.

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 with peer calibration.

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

Experiment design

SQL

Python

Executive communication

Written communication

Attention to detail

Job description

Mercor seeks experienced data scientists to design task-specific grading criteria for real-world deliverables and to score both AI-generated and human work with detailed justifications. You will ensure reproducible, defensible scoring through evidence-based judgment and rapid iteration with senior reviewers.

Ideal candidates have 5+ years in industry data science, plus deep fluency in experiment design, A/B testing, and communicating findings to executives.