R Engineer for Data Analysis and AI Evaluation
Overview
Remote, hourly contract role for an experienced R engineer focused on data analysis tasks in an AI context. You will review AI-generated responses and generate high-quality R content that demonstrates correct reasoning using reproducible workflows such as R Markdown. You’ll assess accuracy, clarity, and adherence to prompts, and identify missteps in statistical methods or data-wrangling within analyses. Document expert explanations and model solutions that showcase proper R usage, then rate and compare AI outputs to guide future work. This engagement has no immediate project and offers opportunities to join SME Careers for future roles within the SuperAnnotate network.
What You'll Do8
- 1Review AI-generated responses and craft accompanying R code explanations that illustrate correct reasoning and problem solving.
- 2Build end-to-end analyses in R that combine data cleaning, exploration, modeling, and visualization to benchmark AI outputs.
- 3Evaluate AI replies for statistical validity, flag inconsistencies, and document reasons for corrections.
- 4Write clear, expert-level explanations and model solutions showing proper R usage and reproducible workflows via R Markdown.
- 5Compare multiple AI-generated solutions, rate them on accuracy and reasoning, and summarize findings for internal or client-ready reports.
- 6Contribute to reproducible research artifacts using R Markdown or Quarto to capture workflows.
- 7Collaborate with data science teammates to align AI outputs with domain standards and best practices.
- 8Ensure code quality via basic testing with testthat and version control with git.
Requirements10
- 12+ years of hands-on experience using R for data analysis, statistics, or data science.
- 2Strong proficiency in R programming including data wrangling, functional programming patterns, and writing reusable functions or packages.
- 3Solid grounding in applied statistics including regression, inference, and model validation with practical experience in R.
- 4Experience building end-to-end analyses in R that include data cleaning, exploratory data analysis, modeling, and visualization.
- 5Familiarity with common R ecosystems such as tidyverse, data.table, and ggplot2 and the ability to choose appropriate tools for the task.
- 6Professional experience in a data-focused role such as data scientist, statistician, quantitative analyst, or similar.
- 7Bachelor’s degree in Statistics, Mathematics, Computer Science, or a closely related quantitative field.
- 8Significant experience using LLMs to assist with coding, analysis design, and code review in R.
- 9Excellent English writing skills with the ability to document analyses and explain complex statistical ideas clearly to non-experts.
- 10Prior experience with AI data training or model evaluation is strongly preferred; minimum C1 English proficiency.
Who Should Apply
R-focused data professionals with at least two years of hands-on experience in data analysis or data science will thrive here. Candidates should demonstrate solid R programming, data wrangling, and reproducible reporting with R Markdown. Those who have worked with LLM-assisted coding and can articulate statistical methods clearly will stand out. This role may be less suitable for applicants lacking practical R experience or those without familiarity with reproducible workflows or AI data evaluation. A remote, contract setting suits self-motivated professionals who can structure work independently and communicate technical results clearly.
Salary Insight
$55/hr. This remote, hourly contract aligns with mid-senior R engineers performing data analysis and AI evaluation; pay is discussed upfront for qualified applicants.
Location
Required Skills
Application Tip
Highlight at least two projects where you used LLMs to assist R coding and delivered reproducible analyses with R Markdown; include metrics or qualitative outcomes showing reasoning quality and auditability.
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How your application is processed
1Application received
Your resume and details are logged the moment you apply.
2ATS + eligibility screening
We check your profile against the role’s skills, seniority, and requirements.
3Employer sees qualified profiles only
Only candidates who clear screening move forward.
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