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Statistical Modeling Researcher

Handshake AI

You'll draw on your deep expertise in statistical theory, methodology, and applied modeling to evaluate AI-generated content and provide feedback that helps AI better understand statistical research and…

Work arrangement & location
Remote · Location requirements need confirmation
Location and residence requirements
Residence
Conflicting requirements
Residence
Some source requirements are unclear; confirm with the employer.

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Degree filters: Bachelor's, Master's, Ph.Ds, Postdocs
Hours
5–20 hours per week

Employer description and requirements

Overview

Handshake is looking for statistics and statistical modeling researchers to support AI research through flexible, hourly contract work. This is not a traditional job. You'll draw on your deep expertise in statistical theory, methodology, and applied modeling to evaluate AI-generated content and provide feedback that helps AI better understand statistical research and methodology.

This is an ongoing, project-based opportunity you can take on alongside anything else you have going on.

Details

  • This project involves using your research expertise and academic knowledge to create expert-level training data and evaluate AI-generated responses for accuracy and relevance. No prior AI experience required.
  • Fully remote with a flexible, asynchronous schedule and no minimum hour requirement; most contributors work approximately 5–20 hours per week when participating in an active project.
  • Placement depends on current project needs, with opportunities to be considered for future projects as they become available.

Qualifications

  • PhD in Statistics, Biostatistics, Applied Statistics, or a related field from a top 100 US university
  • Research background in areas such as:
    • Statistical Theory or Methodology
    • Statistical Computation or Machine Learning
    • Applied Statistics or Statistics Applications
  • Familiarity with arxiv.org, particularly the Statistics repository (stat)
  • Strong written communication skills, attention to detail, and the ability to work independently and asynchronously with AI research teams.