Data Science QA Lead

The work

As a Data Science QA Lead, you will review AI-generated data science content and trainer quality work. You will assess technical accuracy, methodology, reproducibility, business context, instruction following, and rubric adherence, then write feedback that helps improve quality across projects.

• Review data science explanations, Python, R, and SQL snippets, modeling workflows, dashboards, experiment designs, and step-by-step reasoning.
• Check for data leakage, flawed assumptions, incorrect metrics, weak methods, non-reproducible code, and misleading conclusions.
• Communicate guideline changes and workflow updates to trainers and QAs.
• Create and maintain style guides, trackers, FAQs, examples, honeypots, calibration tasks, and onboarding materials.
• Support contributor onboarding and training calls, and help improve QA processes.

What it pays and takes

This is a part-time, hourly remote contractor role. The work requires strong technical judgment, clear written English, and the ability to organize detailed quality resources.

• Pay: Advertised rate of up to $110 USD per hour.
• Time: 20+ hours per week.
• Location: United States.
• Language: Strong English communication skills.
• Education: A degree in data science, statistics, computer science, machine learning, mathematics, economics, engineering, or a related quantitative field.
• Experience: At least three years in data science, analytics, machine learning, statistical modeling, experimentation, data engineering, technical review, or data science education.
• Knowledge: Statistics, model evaluation, experimentation, regression, classification, clustering, and validation methods.
• Tools: Python, pandas, NumPy, scikit-learn, SQL, Jupyter, matplotlib, R, Spark, Git, MLflow, notebooks, dashboards, and cloud or data platforms.
• Preferred background: AI training, data annotation, LLM evaluation, data science QA, rubric-based technical review, or support for remote teams of trainers, annotators, analysts, data scientists, engineers, educators, or QAs.
• Organization: Comfort with Discord, Google Sheets, Google Docs, trackers, dashboards, GitHub, and project management systems.

How it works

Apply on OpenTrain with your resume, then complete the application on the hiring site.

About AI training work

AI training is the human work behind artificial intelligence, including reviewing model answers, checking code and reasoning, and preparing examples that help systems improve. OpenTrain helps people find and build careers in this field, where experienced contributors use subject knowledge to assess quality and shape how AI systems behave.