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3 часа назад

HEOR Intern (Real-World Evidence)

3 200$
Формат работы
remote (только USA)
Тип работы
fulltime
Грейд
trainee
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR

HEOR Intern (Real-World Evidence): Supporting real-world evidence studies and streamlining internal research processes with an accent on protocol development, data programming, and literature reviews. Focus on interpreting quantitative and qualitative findings and developing interactive summaries of healthcare analyses.

Location: Remote (United States)

Salary: $20 per hour

Company

hirify.global provides specialized research and analytics for the life sciences and pharmaceutical industries.

What you will do

  • Streamline internal processes and investigate optimal research techniques to improve efficiency.
  • Support real-world evidence studies, including protocol development, data programming, and results analysis.
  • Conduct literature reviews on diverse healthcare topics.
  • Develop interactive summaries of RWE analyses and communicate findings to internal and external audiences.
  • Contribute to reports, results tables, presentations, and peer-reviewed manuscripts.
  • Participate in client-facing activities and provide administrative project support.

Requirements

  • Must be currently enrolled in a public health, economics, data science, life sciences, or healthcare-related undergraduate or graduate program.
  • Must be based in the United States.
  • Research experience in epidemiology, public health, health services research, or health policy.
  • Foundational knowledge of observational study designs, measures of association, and bias/confounding.
  • Proficiency with statistical programming tools such as R, SQL, SAS, or similar platforms.
  • Proficiency with Microsoft Office.

Nice to have

  • Enrolled in a life sciences related advanced degree program.
  • Formal training in quantitative methodologies and strong understanding of the scientific method.
  • Familiarity with interactive data visualization tools such as R Shiny, Power BI, or Tableau.
  • Experience working in virtual AWS environments, Git, and Github.

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