Назад
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7 дней назад

HEOR Intern, Real-World Evidence

20$
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): Help streamline internal processes and support ongoing research projects in healthcare analytics with an accent on real-world evidence studies and epidemiologic methods. Focus on developing protocols, programming data analyses, creating interactive tools, and communicating quantitative findings to stakeholders.

Location: Remote, United States

Salary: $20 USD

Company

hirify.global provides real-world evidence services for healthcare and life sciences research.

What you will do

  • Streamline internal processes by investigating research techniques, updating tools and documentation, and refining interactive real-world evidence tools.
  • Support research projects through literature reviews, protocol development, data programming, and results interpretation.
  • Develop interactive summaries of analyses and contribute to reports, presentations, tables, or peer-reviewed manuscripts.
  • Participate in client-facing activities and provide administrative project support.

Requirements

  • Enrolled in undergraduate or graduate program in public health, epidemiology, biostatistics, data science, economics, life sciences, or healthcare-related field.
  • Proven interest in public health, life sciences, or pharmaceutical research and analytics.
  • Research experience in epidemiology, public health, health services research, health policy, or economics.
  • Foundational knowledge of epidemiologic concepts including study designs, measures of association, bias, and confounding.
  • Familiarity with statistical programming tools such as R, SQL, SAS or similar.
  • Proficiency with Microsoft Office; strong academic record; detail-oriented with interpersonal and time management skills.

Nice to have

  • Enrolled in advanced life sciences degree program.
  • Strong understanding of scientific method and quantitative methodologies.
  • Familiarity with data visualization tools like R Shiny, Power BI, Tableau.
  • Experience with AWS, Git, and GitHub.

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