R Quality Assurance Lead

About Open Train

Open Train is the #1 platform for finding and building careers in AI training and data labeling. Open Train AI is recruiting for this contract role and helps contributors build a credible portfolio while working on projects that shape how modern AI systems perform.

• Remote contract opportunity with Open Train AI
• Work on specialized R and data-analysis quality assurance
• Build experience in a fast-growing AI training industry

AI training is the human side of building artificial intelligence. Contributors review examples, write feedback, and evaluate model outputs so AI systems can become more accurate, useful, and reliable. In this role, your R and statistics expertise will help improve generated code and analytical reasoning.

• Evaluate AI-generated programming and data-analysis content
• Identify inaccurate methods, unsupported claims, and non-reproducible workflows
• Help establish consistent standards for AI training contributors

Open Train is seeking an R Quality Assurance Lead to review AI-generated R code, statistical explanations, visualizations, data-wrangling steps, and modeling workflows. You will assess accuracy, reproducibility, clarity, and adherence to project rubrics while providing precise written feedback.

The role also includes maintaining R-specific standards, supporting trainer and QA questions, and contributing practical resources such as style guides, examples, trackers, FAQs, honeypots, and onboarding materials.

• Intermediate experience level
• Contractor and part-time engagement
• United States only
• 20+ hours per week
• Up to $65 per hour
• English-language work

You will combine hands-on R programming knowledge with careful statistical review. Your feedback will help contributors follow project guidelines and improve the quality and consistency of R-focused AI training work.

• Review R programming and data-analysis items for correctness and clarity
• Check statistical validity, package usage, debugging accuracy, readability, and visualization quality
• Provide precise written feedback to contributors
• Help contributors follow project guidelines
• Support R-specific coordination
• Maintain trackers, FAQs, and onboarding assets
• Flag misleading statistical claims, invalid methods, non-reproducible workflows, and hallucinated functions
• Improve QA processes using recurring gaps and trainer performance patterns

You should have at least three years of experience using R for data analysis, statistics, research, analytics, teaching, coding, or technical review. Strong English skills are required for following guidelines and writing clear, actionable feedback.

• 3+ years of experience using R in a relevant setting
• Strong knowledge of R syntax, data frames, vectors, functions, lists, factors, and missing data
• Proficiency with tidyverse and base R workflows
• Understanding of statistical modeling and visualization
• Ability to identify incorrect statistical assumptions and invalid package usage
• Ability to spot data leakage, flawed transformations, and misleading charts
• Ability to evaluate reproducibility and technical accuracy

The following experience is preferred and may help you contribute to R quality assurance, documentation, and remote review operations.

• dplyr, tidyr, and ggplot2
• R Markdown or Quarto
• Git and reproducible workflows
• Reviewing or teaching R, analytics, or technical work
• Leading remote QA, trainer, or reviewer teams

Every major AI system depends on people who prepare, review, and improve the data and examples used for training. By applying your R and statistical expertise, you can directly influence whether AI-generated analyses are accurate, understandable, and dependable.

• Contribute to cutting-edge AI development
• Use specialized technical expertise in flexible remote work
• Help shape how AI handles R programming and statistical analysis