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AI Clinical Trial Site Selection Optimizer

James Yamamoto

Full-time · Job · New_York

About the role

Our mission is to shorten the time it takes life-saving drugs to reach patients, and one of the biggest hidden delays in that process is picking the wrong trial sites. Sites that under-enroll or drop out mid-study can add months to a trial timeline. This role exists to fix that. You'll build predictive models that score candidate trial sites on historical enrollment velocity, dropout risk, and investigator track record, feeding directly into how our clinical operations team plans multi-site studies. The models need to hold up to scrutiny from statisticians and regulatory reviewers, not just perform well on a holdout set. You'll work closely with clinical operations and biostatistics, and your models will directly influence which hospitals and research centers get selected for trials worth tens of millions of dollars.

Responsibilities

  • Build and validate site-selection scoring models using historical trial data
  • Partner with biostatistics to ensure models meet regulatory documentation standards
  • Maintain feature pipelines built on AWS covering enrollment, dropout and investigator history
  • Present model rationale and limitations to clinical operations leadership
  • Continuously monitor model performance against realized trial outcomes

Requirements

  • 5+ years applying machine learning to healthcare or clinical operations data
  • Strong scikit-learn and statistical modeling background
  • Experience working with regulated or auditable model pipelines
  • SQL fluency and comfort with AWS-based data infrastructure

Benefits

  • Remote position with quarterly on-site collaboration weeks
  • Comprehensive health, dental and vision coverage
  • Equity in a Series C company
  • Generous parental leave

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$160k – $200k / year

AI Expertise

AI & Machine Learning Engineers data science & analytics

Skills

python scikit-learn sql statistics aws

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