Statistical Modeling Researcher - Remote Part-Time

What You'll Do6

• Build expert-level training prompts and scenarios drawn from real statistical modeling projects and methods.
• Assess AI responses for mathematical accuracy, methodological soundness, and relevance to practical statistical analysis.
• Write structured feedback that names errors, missing assumptions, and weak reasoning in model outputs.
• Use current arxiv stat research to shape question design and evaluation criteria.
• Check calculations and modeling claims with tools such as R, Python, or Stan.
• Set your own schedule and finish tasks at a pace that works for you, with no minimum hour requirement.

Requirements5

• PhD in statistics, biostatistics, econometrics, or a related field from a top 100 US university.
• Deep command of at least one area: Bayesian inference, time series analysis, causal inference, or regression modeling.
• Regular use of arxiv.org (stat) to follow new research.
• Hands-on skill with R, Python, Stan, or comparable statistical software.
• Strong writing, close attention to detail, and comfort working alone in a remote asynchronous setting.

Who Should Apply

The strongest candidate holds a statistics, biostatistics, econometrics, or related PhD from a top 100 US university and uses Bayesian inference, time series, causal inference, or regression modeling in current research. You also read arxiv stat papers and can write precise critiques in R, Python, or Stan. This fellowship suits someone who wants flexible project work alongside a primary academic or industry role. The role does not suit researchers who need fixed hours, close supervision, or frequent live collaboration. Candidates often lose fit when they list statistical methods without showing hands-on research use, or when their written feedback lacks clear structure and evidence.

Salary Insight