Statistical Analysis AI Evaluation Expert

About OpenTrain

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About AI Training Work

AI training is the human side of building artificial intelligence. Experts prepare examples, evaluate model responses, and check whether AI systems produce accurate, useful, and well-reasoned results.

In this project, your statistical expertise will help benchmark AI models against realistic research workflows. Your analysis and feedback can shape how models handle statistical methods, numerical results, and research reporting.

The Role

OpenTrain AI is recruiting a Statistical Analysis AI Evaluation Expert to build realistic statistical analysis environments used to benchmark AI models. You will create research datasets and study-design briefs, execute reference analyses, define numerical checks for statistical outputs, and validate generated tasks.

The work covers descriptive and inferential statistics, hypothesis testing, regression, ANOVA, ANCOVA, non-parametric methods, reliability analysis, visualization, and research reporting. This is a remote hourly contractor engagement expected to run for five weeks, with possible extension based on project requirements.

• Engagement type: Remote, part-time contractor
• Time requirement: 20+ hours per week
• Expected duration: 5 weeks
• Extension: Possible based on project requirements
• Hourly rate: Not disclosed
• Work location: Worldwide

What You’ll Do

You will design and review statistical evaluation tasks that accurately represent real research work. You will also explain why an analysis is technically correct or identify where a model-generated result, transformation, assumption check, or interpretation needs improvement.

• Map workflows for descriptive and inferential analysis, hypothesis testing, regression, ANOVA, ANCOVA, non-parametric testing, reliability analysis, and visualization.
• Create realistic unclean survey datasets, clinical trial tables, psychological assessment data, and study-design briefs.
• Perform end-to-end analyses in jamovi or JASP and record reference execution traces.
• Define verification criteria for p-values, test statistics, effect sizes, regression coefficients, and APA-style summary tables.
• Review tasks for accuracy, solvability, methodological appropriateness, and completeness.
• Assess data transformations, assumption tests, post-hoc analyses, statistical models, and written interpretations.

Required Qualifications

This role is listed at the entry level, but it requires substantial hands-on statistical capability and a professional background in statistics, biostatistics, quantitative research, psychometrics, or data analytics. You must be able to validate results with mathematical and numerical precision and communicate statistical reasoning clearly in written English.

• Professional background in statistics, biostatistics, quantitative research, psychometrics, or data analytics.
• Advanced hands-on experience with jamovi or JASP, or strong experience with JMP or SPSS.
• Ability to perform and interpret regression, ANOVA, ANCOVA, and non-parametric analyses.
• Understanding of descriptive and inferential statistics, t-tests, MANOVA, linear and logistic regression, Mann-Whitney tests, and Kruskal-Wallis tests.
• Knowledge of assumption testing, model diagnostics, effect sizes, and post-hoc testing.
• Precision in validating p-values, test statistics, regression coefficients, and other statistical results.
• Clear written English for unambiguous statistical research briefs.
• Familiarity with APA-style reporting and publication-quality tables and plots.

Helpful Experience

The following background is helpful for working across statistical tools, validating reference results, and preparing realistic research tasks.

• Experience with R syntax mode in jamovi or JASP.
• Familiarity with the jmv package or R code mode.
• Experience with cross-tool result validation.
• Knowledge of statistical data cleaning or transformation workflows.
• Familiarity with research, clinical, psychological, or survey datasets.

Why Join This AI Evaluation Project

AI training and data-labeling work is a flexible way to contribute to cutting-edge technology from anywhere with a computer and internet connection. Specialist projects like this one let contributors apply professional knowledge directly to how advanced AI systems are evaluated and improved.

Through OpenTrain, you can build a profile around your AI training experience, discover projects aligned with your skills, and develop a durable portfolio in a fast-growing industry.

• Work remotely from anywhere in the world.
• Apply statistical expertise to challenging AI evaluation tasks.
• Contribute to benchmarks covering realistic research analyses.
• Build experience in statistical AI model evaluation.
• Work on a flexible part-time contractor engagement.

How to Apply

Create a free OpenTrain account and apply for this Statistical Analysis AI Evaluation Expert engagement. Make sure your profile clearly reflects your statistical background, experience with supported analysis software, and ability to produce precise research documentation.

• Highlight experience with jamovi, JASP, JMP, or SPSS.
• Describe your work with regression, ANOVA, ANCOVA, non-parametric tests, and diagnostics.
• Showcase statistical validation, APA-style reporting, and research dataset experience.