This is not a traditional job — you'll draw on your hands-on expertise in Bayesian inference, time series analysis, causal modeling, or applied statistics to evaluate AI-generated content and provide feedback that helps AI better understand advanced statistical reasoning and methodology.

This is an ongoing, project-based opportunity you can take on alongside your current work.

Complete tasks at your own pace with no set schedule or minimum hour requirement.

• Use your domain expertise to create expert-level training questions and scenarios based on real statistical modeling research and methods.
• Review and evaluate AI-generated responses for accuracy and relevance to real-world statistical analysis and methodology.
• Provide structured written feedback to help improve AI model performance.

• PhD in Statistics, Biostatistics, Econometrics, or a related field from a top 100 US university.
• Deep expertise in one or more areas such as Bayesian inference, time series analysis, causal inference, or regression modeling.
• Active use of arxiv.org (stat) to stay current with research.
• Proficiency with R, Python, Stan, or similar tools.
• Strong written communication skills, attention to detail, and the ability to work independently in a remote, asynchronous environment.

Work arrangement: Fully remote

Eligible countries: United States