Remote Data Scientist Evaluator (Contractor)

YO IT Consulting; Washington (Washington County); On-site; USD 83,000 - 165,000; Part time

Job summary

YO IT Consulting is seeking a Data Scientist contractor for remote work with a leading AI research organization. You will design task-specific grading criteria and provide rigorous written justifications for scores on real-world data science deliverables.

You will evaluate AI-generated and human work samples, applying evidence-based judgment and incorporating feedback from senior reviewers to iterate efficiently.

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.

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

5+ years data science

Experiment design

SQL

Python

Executive communication

Tools

SQL

Python

Job description

YO IT Consulting is seeking a Data Scientist contractor for remote work with a leading AI research organization. You will design task-specific grading criteria and provide rigorous written justifications for scores on real-world data science deliverables.

You will evaluate AI-generated and human work samples, applying evidence-based judgment and incorporating feedback from senior reviewers to iterate efficiently.